diff --git a/NumPy.ipynb b/NumPy.ipynb
deleted file mode 100644
index 2825118..0000000
--- a/NumPy.ipynb
+++ /dev/null
@@ -1,2388 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "3ef254f6",
-   "metadata": {},
-   "source": [
-    "![GitHub Community GITAM](https://raw.githubusercontent.com/srinijadharani/GitHub-Campus-Code-of-Conduct/main/github_landscape.png)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "156c3891",
-   "metadata": {},
-   "source": [
-    "# Numpy"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "76b24b7a",
-   "metadata": {},
-   "source": [
-    "### What is Numpy?\n",
-    "NumPy is an open-source Python package. It stands for **Numerical Python**. It is a library consisting of multidimensional array objects and a collection of routines for processing of array. Using NumPy, mathematical and logical operations on arrays can be performed.\n",
-    "\n",
-    "Check out Numpy's repository on GitHub [here](https://github.com/numpy/numpy)\n",
-    "\n",
-    "### Installation:\n",
-    "- If you use pip, install Numpy using the following command:<br>\n",
-    "`pip install numpy`\n",
-    "- If you installed Anaconda, then Numpy comes pre-installed.\n",
-    "\n",
-    "### Why use Numpy?\n",
-    "NumPy arrays are faster and more compact than Python lists. An array consumes less memory and is convenient to use. NumPy uses much less memory to store data and it provides a mechanism of specifying the data types. This allows the code to be optimized even further.\n",
-    "\n",
-    "### Importing:\n",
-    "You can import Numpy in your program using the following command: <br>\n",
-    "`import numpy as np`"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "d82f188f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "e05a80fa",
-   "metadata": {},
-   "source": [
-    "Check the version of Numpy you're using right now:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "8668879e",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'1.20.3'"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.__version__"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "4423b8f9",
-   "metadata": {},
-   "source": [
-    "See the configuration of Numpy you're using right now:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "35ddbafc",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "blas_mkl_info:\n",
-      "    libraries = ['mkl_rt']\n",
-      "    library_dirs = ['C:/Users/srini/anaconda3\\\\Library\\\\lib']\n",
-      "    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]\n",
-      "    include_dirs = ['C:/Users/srini/anaconda3\\\\Library\\\\include']\n",
-      "blas_opt_info:\n",
-      "    libraries = ['mkl_rt']\n",
-      "    library_dirs = ['C:/Users/srini/anaconda3\\\\Library\\\\lib']\n",
-      "    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]\n",
-      "    include_dirs = ['C:/Users/srini/anaconda3\\\\Library\\\\include']\n",
-      "lapack_mkl_info:\n",
-      "    libraries = ['mkl_rt']\n",
-      "    library_dirs = ['C:/Users/srini/anaconda3\\\\Library\\\\lib']\n",
-      "    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]\n",
-      "    include_dirs = ['C:/Users/srini/anaconda3\\\\Library\\\\include']\n",
-      "lapack_opt_info:\n",
-      "    libraries = ['mkl_rt']\n",
-      "    library_dirs = ['C:/Users/srini/anaconda3\\\\Library\\\\lib']\n",
-      "    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]\n",
-      "    include_dirs = ['C:/Users/srini/anaconda3\\\\Library\\\\include']\n"
-     ]
-    }
-   ],
-   "source": [
-    "np.show_config()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "755884ce",
-   "metadata": {},
-   "source": [
-    "### How can you create a Numpy Array?<br>\n",
-    "We can directly create a Numpy Array by converting a list or a list of lists:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "8abc685b",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array(['1', '6', 'numpy', '9.7'], dtype='<U32')"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "list1 = [1, 6, \"numpy\", 9.7] # simple Python list\n",
-    "# converting this list into a Numpy array\n",
-    "np.array(list1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "1cf598d6",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([['1', '2', '3'],\n",
-       "       ['four', 'five', 'six'],\n",
-       "       ['7.8', '9.0', '10.1']], dtype='<U32')"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "matrix1 = [[1, 2, 3], [\"four\", \"five\", \"six\"], [7.8, 9.0, 10.1]]\n",
-    "# we can even convert a list of lists (a matrix) into a numpy array\n",
-    "np.array(matrix1)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "0a42ddaa",
-   "metadata": {},
-   "source": [
-    "**Note:** If you're wondering what '<U32' means:<br>\n",
-    "<: little endian - specifies the byte order<br>\n",
-    "U: Unicode string<br>\n",
-    "32: a string of 32 characters<br>\n",
-    "So, `dtype='<U32'` means a little-endian Unicode string of 32 characters."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "0b9153d8",
-   "metadata": {},
-   "source": [
-    "You can also create a numpy array using the following functions:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "ae861776",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.arange(0, 10)\n",
-    "# arange() creates an array of evenly spaced values within a given interval"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "4fe5cc76",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([1, 2, 3, 4, 5, 6, 7, 8, 9])"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.arange(1, 10)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "0420b95a",
-   "metadata": {},
-   "source": [
-    "`arange()` works similar to the `range()` function in Python. You can even add a step as one of the parameters.<br>\n",
-    "Syntax:\n",
-    "`arange(start, stop, step)`"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "faeb2ccb",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([1, 3, 5, 7, 9])"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.arange(1, 11, 2)\n",
-    "# creates an array of odd numbers between 1 and 11 (1 inclusive, 11 exclusive)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "85108fd2",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 2,  4,  6,  8, 10])"
-      ]
-     },
-     "execution_count": 9,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.arange(2, 11, 2)\n",
-    "# creates an array of even nuumbers between 2 and 11 (2 inclusive, 11 exclusive)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "2eb0cfeb",
-   "metadata": {},
-   "source": [
-    "You can create an array of zeros using the `zeros()` function.<br>\n",
-    "Syntax: `zeros(n)` or `zeros((n, m))`. 'n and m' are the number of zeros you want in your array. Using n alone would return a 1D array. (n, m) returns a 2D array of zeros.\n",
-    "\n",
-    "**Note:** Remember to pass (n, m) as a tuple."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "id": "92974a30",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.zeros(10)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "id": "a4166fc7",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[0., 0., 0., 0., 0.],\n",
-       "       [0., 0., 0., 0., 0.]])"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.zeros((2, 5))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "id": "45b83c2e",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[0., 0., 0., 0., 0.],\n",
-       "       [0., 0., 0., 0., 0.],\n",
-       "       [0., 0., 0., 0., 0.],\n",
-       "       [0., 0., 0., 0., 0.],\n",
-       "       [0., 0., 0., 0., 0.]])"
-      ]
-     },
-     "execution_count": 12,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.zeros((5, 5))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "51da657f",
-   "metadata": {},
-   "source": [
-    "Similar to zeros(), there is ones(). This function is used to create a 1D or 2D array of ones."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "id": "36f89c83",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([1., 1.])"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.ones(2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "id": "e36686e7",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[1., 1., 1., 1., 1., 1., 1., 1.],\n",
-       "       [1., 1., 1., 1., 1., 1., 1., 1.],\n",
-       "       [1., 1., 1., 1., 1., 1., 1., 1.]])"
-      ]
-     },
-     "execution_count": 14,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.ones((3, 8))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "id": "81df1003",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[1., 1., 1., 1.],\n",
-       "       [1., 1., 1., 1.],\n",
-       "       [1., 1., 1., 1.],\n",
-       "       [1., 1., 1., 1.]])"
-      ]
-     },
-     "execution_count": 15,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.ones((4, 4))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "c630e7e1",
-   "metadata": {},
-   "source": [
-    "To find the memory size of a numpy array, use the following formula:<br>\n",
-    "`Memory size = size of the array * size of the items in the array`"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "id": "fb7cd366",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "44 bytes\n"
-     ]
-    }
-   ],
-   "source": [
-    "arr = np.arange(1, 12)\n",
-    "print(\"%d bytes\" %(arr.size * arr.itemsize))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "id": "a47f0395",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "11"
-      ]
-     },
-     "execution_count": 17,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr.size"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "id": "5e55e106",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "4"
-      ]
-     },
-     "execution_count": 18,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr.itemsize"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "id": "d106a594",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "arr1 = np.array([\"one\", \"two\", \"three\", \"four\"])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "id": "0615b9cc",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "4"
-      ]
-     },
-     "execution_count": 20,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr1.size"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "id": "4a0d0a48",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "20"
-      ]
-     },
-     "execution_count": 21,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr1.itemsize"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "5c45eb6e",
-   "metadata": {},
-   "source": [
-    "To create an array of **evenly spaced integers** over a specified interval, use the `linspace()` function."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "id": "043ab983",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 0. ,  2.5,  5. ,  7.5, 10. ])"
-      ]
-     },
-     "execution_count": 22,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.linspace(0, 10, 5)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "id": "6070b0a8",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 0.        ,  0.41666667,  0.83333333,  1.25      ,  1.66666667,\n",
-       "        2.08333333,  2.5       ,  2.91666667,  3.33333333,  3.75      ,\n",
-       "        4.16666667,  4.58333333,  5.        ,  5.41666667,  5.83333333,\n",
-       "        6.25      ,  6.66666667,  7.08333333,  7.5       ,  7.91666667,\n",
-       "        8.33333333,  8.75      ,  9.16666667,  9.58333333, 10.        ])"
-      ]
-     },
-     "execution_count": 23,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.linspace(0, 10, 25)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "id": "2301a563",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([  0.        ,  22.22222222,  44.44444444,  66.66666667,\n",
-       "        88.88888889, 111.11111111, 133.33333333, 155.55555556,\n",
-       "       177.77777778, 200.        ])"
-      ]
-     },
-     "execution_count": 24,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.linspace(0, 200, 10)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "1278453a",
-   "metadata": {},
-   "source": [
-    "The `eye()` function is used to create an identity matrix of a given size."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
-   "id": "7aec8e59",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[1., 0., 0., 0., 0.],\n",
-       "       [0., 1., 0., 0., 0.],\n",
-       "       [0., 0., 1., 0., 0.],\n",
-       "       [0., 0., 0., 1., 0.],\n",
-       "       [0., 0., 0., 0., 1.]])"
-      ]
-     },
-     "execution_count": 25,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.eye(5)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
-   "id": "30d8ef4d",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[1., 0., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
-       "       [0., 1., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
-       "       [0., 0., 1., 0., 0., 0., 0., 0., 0., 0.],\n",
-       "       [0., 0., 0., 1., 0., 0., 0., 0., 0., 0.],\n",
-       "       [0., 0., 0., 0., 1., 0., 0., 0., 0., 0.],\n",
-       "       [0., 0., 0., 0., 0., 1., 0., 0., 0., 0.],\n",
-       "       [0., 0., 0., 0., 0., 0., 1., 0., 0., 0.],\n",
-       "       [0., 0., 0., 0., 0., 0., 0., 1., 0., 0.],\n",
-       "       [0., 0., 0., 0., 0., 0., 0., 0., 1., 0.],\n",
-       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 1.]])"
-      ]
-     },
-     "execution_count": 26,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.eye(10)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "fe45ade0",
-   "metadata": {},
-   "source": [
-    "Numpy has the **random** module which has a lot of useful functions.\n",
-    "\n",
-    "**Note:** Random number does not mean a different number every time. Random means something that can not be predicted logically."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "ed84082a",
-   "metadata": {},
-   "source": [
-    "`rand(x)` or `rand(x, y)` - creates an array of the given shape and populates it with random samples from a uniform distribution over [0, 1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 27,
-   "id": "66cb6cb6",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([0.90686041, 0.68339155, 0.25263953, 0.52888379, 0.6522411 ,\n",
-       "       0.08040521, 0.95468398, 0.764556  , 0.21074499, 0.78057812])"
-      ]
-     },
-     "execution_count": 27,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.random.rand(10)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 28,
-   "id": "80d266b2",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[0.53073878, 0.2884517 , 0.65916252, 0.22842514],\n",
-       "       [0.03030595, 0.30790469, 0.15688523, 0.95489973],\n",
-       "       [0.4205393 , 0.27544475, 0.18495732, 0.08423577],\n",
-       "       [0.26796152, 0.49485765, 0.32901431, 0.06760323]])"
-      ]
-     },
-     "execution_count": 28,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.random.rand(4, 4)\n",
-    "# rand - uniform distribution"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "0912b613",
-   "metadata": {},
-   "source": [
-    "`randn(x)` or `randn(x, y)` - returns an array from the standard normal distribution."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
-   "id": "d0343ea7",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7708972375694806"
-      ]
-     },
-     "execution_count": 29,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.random.randn()\n",
-    "# one value"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "id": "397dfafb",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 0.10344622, -1.55634666, -0.33777462, -0.42138101])"
-      ]
-     },
-     "execution_count": 30,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.random.randn(4)\n",
-    "# 4 values"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 31,
-   "id": "158e9bc1",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[-0.11432184, -0.47291981,  0.06279605],\n",
-       "       [-1.18945243, -0.90578155, -1.61738795],\n",
-       "       [ 0.45875176,  0.52117105,  0.99144616],\n",
-       "       [ 0.24096445,  0.76590718, -0.31749352]])"
-      ]
-     },
-     "execution_count": 31,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.random.randn(4, 3)\n",
-    "# a matrix of size 4, 3"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "e2bf3b55",
-   "metadata": {},
-   "source": [
-    "`randint()` - returns random integers over the given range and if specified the number of integers"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "id": "0a04e4e8",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "19"
-      ]
-     },
-     "execution_count": 32,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.random.randint(1, 100)\n",
-    "# one integer"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 33,
-   "id": "a19ee4db",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([39, 16, 10, 39, 12, 18, 18, 38, 24, 46])"
-      ]
-     },
-     "execution_count": 33,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.random.randint(1, 50, 10)\n",
-    "# n integers in a given interval"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "1069fa96",
-   "metadata": {},
-   "source": [
-    "`reshape()` - gives a new shape to an array without changing its data."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 34,
-   "id": "17c9b4d0",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "arr2 = np.arange(1, 11)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 35,
-   "id": "84509410",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10])"
-      ]
-     },
-     "execution_count": 35,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr2"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 36,
-   "id": "1b2921fc",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[ 1,  2,  3,  4,  5],\n",
-       "       [ 6,  7,  8,  9, 10]])"
-      ]
-     },
-     "execution_count": 36,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr2.reshape((2, 5))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "78aacdaa",
-   "metadata": {},
-   "source": [
-    "To find the maximum in an array, use `max()`<br>\n",
-    "To find the minimum in an array, use `min()`<br>\n",
-    "To find the index of the maximum in an array, use `argmax()`<br>\n",
-    "To find the index of the minimum in an array, use `argmin()`<br>"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 37,
-   "id": "1c8a468a",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "arr3 = np.random.randint(1, 100, 10)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 38,
-   "id": "90fbd755",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([52,  6, 69, 27, 64, 82, 92, 33, 94, 33])"
-      ]
-     },
-     "execution_count": 38,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr3"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 39,
-   "id": "4167d77d",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "94"
-      ]
-     },
-     "execution_count": 39,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr3.max()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 40,
-   "id": "ed05fa82",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "8"
-      ]
-     },
-     "execution_count": 40,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr3.argmax()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 41,
-   "id": "5e4e1739",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "6"
-      ]
-     },
-     "execution_count": 41,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr3.min()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 42,
-   "id": "a37c602d",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1"
-      ]
-     },
-     "execution_count": 42,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr3.argmin()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "4d3cdf42",
-   "metadata": {},
-   "source": [
-    "To check the shape of an array, use the `shape` attribute<br>\n",
-    "**Note**: `shape` is an attribute, not a function."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 43,
-   "id": "90fd796a",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(10,)"
-      ]
-     },
-     "execution_count": 43,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr3.shape"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 44,
-   "id": "4fea1993",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11]])"
-      ]
-     },
-     "execution_count": 44,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Notice the two sets of brackets\n",
-    "arr.reshape(1, 11)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 45,
-   "id": "62f67dfe",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(1, 11)"
-      ]
-     },
-     "execution_count": 45,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr.reshape(1, 11).shape"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 46,
-   "id": "0e3efe78",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[ 1],\n",
-       "       [ 2],\n",
-       "       [ 3],\n",
-       "       [ 4],\n",
-       "       [ 5],\n",
-       "       [ 6],\n",
-       "       [ 7],\n",
-       "       [ 8],\n",
-       "       [ 9],\n",
-       "       [10],\n",
-       "       [11]])"
-      ]
-     },
-     "execution_count": 46,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr.reshape(11, 1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 47,
-   "id": "328e52c0",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11])"
-      ]
-     },
-     "execution_count": 47,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "c22c1f2a",
-   "metadata": {},
-   "source": [
-    "Check the type of the elements in an array using `dtype` attribute:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 48,
-   "id": "68f0fa50",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "dtype('int32')"
-      ]
-     },
-     "execution_count": 48,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr.dtype"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 49,
-   "id": "f23a3093",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array(['one', 'two', 'three', 'four'], dtype='<U5')"
-      ]
-     },
-     "execution_count": 49,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr1"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 50,
-   "id": "923df5d6",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "dtype('<U5')"
-      ]
-     },
-     "execution_count": 50,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr1.dtype"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 51,
-   "id": "2dcc8147",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10])"
-      ]
-     },
-     "execution_count": 51,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr2"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 52,
-   "id": "12e45998",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "dtype('int32')"
-      ]
-     },
-     "execution_count": 52,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr2.dtype"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 53,
-   "id": "0c60d3b4",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([52,  6, 69, 27, 64, 82, 92, 33, 94, 33])"
-      ]
-     },
-     "execution_count": 53,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr3"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 54,
-   "id": "a77ba328",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "dtype('int32')"
-      ]
-     },
-     "execution_count": 54,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr3.dtype"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "81192df7",
-   "metadata": {},
-   "source": [
-    "# Indexing and Slicing"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 55,
-   "id": "327aab6c",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "arr = np.arange(0, 11)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 56,
-   "id": "aa191e75",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10])"
-      ]
-     },
-     "execution_count": 56,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "496f1713",
-   "metadata": {},
-   "source": [
-    "To extract a part of an array, use the slice `[n:m]` operator."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 57,
-   "id": "8e72be7a",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([0, 1, 2, 3, 4])"
-      ]
-     },
-     "execution_count": 57,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr[0:5]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 58,
-   "id": "8c3f1683",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([1, 2, 3, 4, 5, 6, 7, 8, 9])"
-      ]
-     },
-     "execution_count": 58,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr[1:10]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 59,
-   "id": "6f6ad714",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10])"
-      ]
-     },
-     "execution_count": 59,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr[0:]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 60,
-   "id": "40ccf0cb",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 5,  6,  7,  8,  9, 10])"
-      ]
-     },
-     "execution_count": 60,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr[5:]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "a4a77144",
-   "metadata": {},
-   "source": [
-    "To make a copy of an existing array, use the `copy()` function."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 61,
-   "id": "982dfe99",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "arr_copy = arr.copy()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 62,
-   "id": "95fd9147",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10])"
-      ]
-     },
-     "execution_count": 62,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr_copy"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 63,
-   "id": "7f97e48c",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "arr_copy[:] = 100"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 64,
-   "id": "aef529a5",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100])"
-      ]
-     },
-     "execution_count": 64,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr_copy"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 65,
-   "id": "fb4d3c30",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10])"
-      ]
-     },
-     "execution_count": 65,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 66,
-   "id": "443a9d18",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "arr_2d = np.array(([1, 2, 3], [4, 5, 6], [7, 8, 9]))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 67,
-   "id": "61612ae4",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[1, 2, 3],\n",
-       "       [4, 5, 6],\n",
-       "       [7, 8, 9]])"
-      ]
-     },
-     "execution_count": 67,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr_2d"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 68,
-   "id": "b9c2d2b3",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([4, 5, 6])"
-      ]
-     },
-     "execution_count": 68,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "#Indexing row\n",
-    "arr_2d[1]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "67c70aea",
-   "metadata": {},
-   "source": [
-    "To index a 2d array, the format is `arr_2d[row][col]` or `arr_2d[row, col]`"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 69,
-   "id": "3b1f8c3c",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "4"
-      ]
-     },
-     "execution_count": 69,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr_2d[1][0]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 70,
-   "id": "0a28ba3b",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "4"
-      ]
-     },
-     "execution_count": 70,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr_2d[1,0]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 71,
-   "id": "8b32207b",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[2, 3],\n",
-       "       [5, 6]])"
-      ]
-     },
-     "execution_count": 71,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr_2d[:2,1:]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 72,
-   "id": "791e0f7c",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([7, 8, 9])"
-      ]
-     },
-     "execution_count": 72,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr_2d[2,:]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "db63997e",
-   "metadata": {},
-   "source": [
-    "To select a few elements from a numpy array, use relational operators or logical operators for instance. You can give your own conditions if you want."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 73,
-   "id": "16052685",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "arr = np.arange(1,11)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 74,
-   "id": "38e96ad8",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "arr = np.arange(1,11)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 75,
-   "id": "9f957f8a",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10])"
-      ]
-     },
-     "execution_count": 75,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 76,
-   "id": "778aa2cd",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([False, False, False, False, False, False, False,  True,  True,\n",
-       "        True])"
-      ]
-     },
-     "execution_count": 76,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr > 7"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 77,
-   "id": "2f0731ec",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "dup_arr = arr > 7"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 78,
-   "id": "cc18e602",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 8,  9, 10])"
-      ]
-     },
-     "execution_count": 78,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr[dup_arr]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 79,
-   "id": "1ce2fbb4",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([False, False, False, False, False, False, False,  True,  True,\n",
-       "        True])"
-      ]
-     },
-     "execution_count": 79,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "dup_arr"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "863c3cf6",
-   "metadata": {},
-   "source": [
-    "Numpy supports a lot of arithmetic operations. For example:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 80,
-   "id": "e6b63d98",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "arr = np.arange(0, 10)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 81,
-   "id": "2c64658b",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
-      ]
-     },
-     "execution_count": 81,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 82,
-   "id": "21e0174a",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 0,  2,  4,  6,  8, 10, 12, 14, 16, 18])"
-      ]
-     },
-     "execution_count": 82,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr + arr"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 83,
-   "id": "a2f3120e",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])"
-      ]
-     },
-     "execution_count": 83,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr - arr"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 84,
-   "id": "695833cc",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 0,  1,  4,  9, 16, 25, 36, 49, 64, 81])"
-      ]
-     },
-     "execution_count": 84,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr * arr"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 85,
-   "id": "176d3a92",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\srini\\AppData\\Local\\Temp/ipykernel_116188/3001117470.py:1: RuntimeWarning: invalid value encountered in true_divide\n",
-      "  arr / arr\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "array([nan,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.])"
-      ]
-     },
-     "execution_count": 85,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr / arr"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 86,
-   "id": "fad64120",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 0,  1,  4,  9, 16, 25, 36, 49, 64, 81], dtype=int32)"
-      ]
-     },
-     "execution_count": 86,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr ** 2"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 87,
-   "id": "a8bf1e23",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([  0,   1,   8,  27,  64, 125, 216, 343, 512, 729], dtype=int32)"
-      ]
-     },
-     "execution_count": 87,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr ** 3"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 88,
-   "id": "2c173ea0",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 0,  4,  8, 12, 16, 20, 24, 28, 32, 36])"
-      ]
-     },
-     "execution_count": 88,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr * 4"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 89,
-   "id": "8abb9e23",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\srini\\AppData\\Local\\Temp/ipykernel_116188/1528351372.py:1: RuntimeWarning: divide by zero encountered in true_divide\n",
-      "  1 / arr\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "array([       inf, 1.        , 0.5       , 0.33333333, 0.25      ,\n",
-       "       0.2       , 0.16666667, 0.14285714, 0.125     , 0.11111111])"
-      ]
-     },
-     "execution_count": 89,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "1 / arr"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 90,
-   "id": "4bc89a4f",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([0.        , 1.        , 1.41421356, 1.73205081, 2.        ,\n",
-       "       2.23606798, 2.44948974, 2.64575131, 2.82842712, 3.        ])"
-      ]
-     },
-     "execution_count": 90,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.sqrt(arr)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 91,
-   "id": "410873e7",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([1.00000000e+00, 2.71828183e+00, 7.38905610e+00, 2.00855369e+01,\n",
-       "       5.45981500e+01, 1.48413159e+02, 4.03428793e+02, 1.09663316e+03,\n",
-       "       2.98095799e+03, 8.10308393e+03])"
-      ]
-     },
-     "execution_count": 91,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# calcualting exponential (e^)\n",
-    "np.exp(arr)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 92,
-   "id": "d4b7e532",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "9"
-      ]
-     },
-     "execution_count": 92,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.max(arr)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 93,
-   "id": "c859291e",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 0.        ,  0.84147098,  0.90929743,  0.14112001, -0.7568025 ,\n",
-       "       -0.95892427, -0.2794155 ,  0.6569866 ,  0.98935825,  0.41211849])"
-      ]
-     },
-     "execution_count": 93,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.sin(arr)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 94,
-   "id": "e2bba092",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\srini\\AppData\\Local\\Temp/ipykernel_116188/3120950136.py:1: RuntimeWarning: divide by zero encountered in log\n",
-      "  np.log(arr)\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "array([      -inf, 0.        , 0.69314718, 1.09861229, 1.38629436,\n",
-       "       1.60943791, 1.79175947, 1.94591015, 2.07944154, 2.19722458])"
-      ]
-     },
-     "execution_count": 94,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.log(arr)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "65db4b61",
-   "metadata": {},
-   "source": [
-    "To find the sum of all elements in an array, use the `sum()` function"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 95,
-   "id": "ce13011e",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "45"
-      ]
-     },
-     "execution_count": 95,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr.sum()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 96,
-   "id": "7547b71f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "matrix2 = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 97,
-   "id": "71d30b8c",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[1, 2, 3],\n",
-       "       [4, 5, 6],\n",
-       "       [7, 8, 9]])"
-      ]
-     },
-     "execution_count": 97,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "matrix2"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 98,
-   "id": "a85f7103",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([12, 15, 18])"
-      ]
-     },
-     "execution_count": 98,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "matrix2.sum(axis = 0)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 99,
-   "id": "8f283c94",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 6, 15, 24])"
-      ]
-     },
-     "execution_count": 99,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "matrix2.sum(axis = 1)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "8a29302a",
-   "metadata": {},
-   "source": [
-    "To find the standard deviation of all elements in an array, use the `std()` function"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 100,
-   "id": "79ad8eba",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "2.8722813232690143"
-      ]
-     },
-     "execution_count": 100,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "arr.std()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "04949fbb",
-   "metadata": {},
-   "source": [
-    "**References:**<br>\n",
-    "1. https://www.mygreatlearning.com/blog/python-numpy-tutorial/ - mygreatlearning\n",
-    "2. https://numpy.org/devdocs/user/absolute_beginners.html#:~:text=Why%20use%20NumPy%3F,of%20specifying%20the%20data%20types."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "d43d593c",
-   "metadata": {},
-   "source": [
-    "# the end."
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.7"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/Pandas.ipynb b/Pandas.ipynb
deleted file mode 100644
index 7cc1ecc..0000000
--- a/Pandas.ipynb
+++ /dev/null
@@ -1,5950 +0,0 @@
-{
- "cells": [
-  {
-   "attachments": {
-    "image.png": {
-     "image/png": 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"
-    }
-   },
-   "cell_type": "markdown",
-   "id": "16822a6b",
-   "metadata": {},
-   "source": [
-    "# ![image.png](attachment:image.png)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "532dc69f",
-   "metadata": {},
-   "source": [
-    "# Pandas\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "dbdf719f",
-   "metadata": {},
-   "source": [
-    "## What is Pandas?"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "8dde7fe4",
-   "metadata": {},
-   "source": [
-    "pandas is a Python package that provides fast, flexible, and expressive data structures designed to make working with \"relational\" or \"labeled\" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "95607550",
-   "metadata": {},
-   "source": [
-    "## Installation"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "f6ca1b0b",
-   "metadata": {},
-   "source": [
-    "- If you use pip: "
-   ]
-  },
-  {
-   "cell_type": "raw",
-   "id": "f4e65bd2",
-   "metadata": {},
-   "source": [
-    "pip install pandas"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "3342562c",
-   "metadata": {},
-   "source": [
-    "- if you prefer anaconda"
-   ]
-  },
-  {
-   "cell_type": "raw",
-   "id": "b4269b5a",
-   "metadata": {},
-   "source": [
-    "conda install pandas"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "2593edfb",
-   "metadata": {},
-   "source": [
-    "## Importing pandas"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "7d141b64",
-   "metadata": {},
-   "source": [
-    "You can import Numpy in your program using the following command:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "3a63bf7f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import pandas as pd"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "073b96cc",
-   "metadata": {},
-   "source": [
-    "Check the version of Numpy you're using right now:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "86907a95",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'1.3.4'"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "pd.__version__"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "f1fa2bc4",
-   "metadata": {},
-   "source": [
-    "## Creating data using pandas"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "f31e845f",
-   "metadata": {},
-   "source": [
-    "There are two core objects in pandas: the <b>DataFrame</b> and the <b>Series</b>."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "f546c80a",
-   "metadata": {},
-   "source": [
-    "### Creating a DataFrame"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "e1c45d81",
-   "metadata": {},
-   "source": [
-    "A DataFrame is a table. It contains an array of individual entries, each of which has a certain value. Each entry corresponds to a row (or record) and a column."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "47065b81",
-   "metadata": {},
-   "source": [
-    "Let's take an example. Jack and Jill are discussing about sweet and savoury food. Jack prefers sweet more than savoury and Jill prefers the opposite. Lets create a DataFrame to depict their likes and dislikes."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "6c34d332",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>Jack</th>\n",
-       "      <th>Jill</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>Very yum</td>\n",
-       "      <td>Not my type</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>Awful</td>\n",
-       "      <td>I loved it</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "       Jack         Jill\n",
-       "0  Very yum  Not my type\n",
-       "1     Awful   I loved it"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "pd.DataFrame({'Jack':[\"Very yum\",\"Awful\"],'Jill':[\"Not my type\",'I loved it']})"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "8375b411",
-   "metadata": {},
-   "source": [
-    "Here, we cannot really know what Jack and Jill is talking about. Let's change the indexes from 0,1 to something more informative"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "a2cd0bd9",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>Jack</th>\n",
-       "      <th>Jill</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>Chocolates</th>\n",
-       "      <td>Very yum</td>\n",
-       "      <td>Not my type</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Chips</th>\n",
-       "      <td>Awful</td>\n",
-       "      <td>I loved it</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                Jack         Jill\n",
-       "Chocolates  Very yum  Not my type\n",
-       "Chips          Awful   I loved it"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "pd.DataFrame({'Jack':[\"Very yum\",\"Awful\"],'Jill':[\"Not my type\",'I loved it']},index=[\"Chocolates\",\"Chips\"])"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "46879b20",
-   "metadata": {},
-   "source": [
-    "### Creating Series"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "9ea185ec",
-   "metadata": {},
-   "source": [
-    "A Series, by contrast, is a sequence of data values. If a DataFrame is a table, a Series is a list. And in fact you can create one with nothing more than a list:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "3f841de2",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0    1\n",
-       "1    2\n",
-       "2    3\n",
-       "3    4\n",
-       "dtype: int64"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "pd.Series([1,2,3,4])"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "78f4605e",
-   "metadata": {},
-   "source": [
-    "Let's make it more specific. Lets print a list of items and its available number sold by Grocery A."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "369561b1",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Chocolates    30\n",
-       "Chips         35\n",
-       "Biscuits      29\n",
-       "Name: Grocery A, dtype: int64"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "pd.Series([30,35,29],index=[\"Chocolates\",\"Chips\",\"Biscuits\"],name='Grocery A')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "60823137",
-   "metadata": {},
-   "source": [
-    "## Reading Data files"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "da27591e",
-   "metadata": {},
-   "source": [
-    "Data can be stored in any of a number of different forms and formats. By far the most basic of these is the humble CSV file. When you open a CSV file you get something that looks like this:"
-   ]
-  },
-  {
-   "cell_type": "raw",
-   "id": "4e005612",
-   "metadata": {},
-   "source": [
-    "Product A,Product B,Product C,\n",
-    "30,21,9,\n",
-    "35,34,1,\n",
-    "41,11,11"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "cc27cca7",
-   "metadata": {},
-   "source": [
-    "Let's read a csv file"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "4311938b",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "net_titles = pd.read_csv(\"netflix_titles.csv\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "d60e545e",
-   "metadata": {},
-   "source": [
-    "We can use the <b>shape</b> attribute to check how large the resulting DataFrame is:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "f1bfae8b",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(8807, 12)"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.shape"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "89578694",
-   "metadata": {},
-   "source": [
-    "We can examine the contents of the resultant DataFrame using the head() command, which grabs the first five rows:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "d41cec6b",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>show_id</th>\n",
-       "      <th>type</th>\n",
-       "      <th>title</th>\n",
-       "      <th>director</th>\n",
-       "      <th>cast</th>\n",
-       "      <th>country</th>\n",
-       "      <th>date_added</th>\n",
-       "      <th>release_year</th>\n",
-       "      <th>rating</th>\n",
-       "      <th>duration</th>\n",
-       "      <th>listed_in</th>\n",
-       "      <th>description</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>s1</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Dick Johnson Is Dead</td>\n",
-       "      <td>Kirsten Johnson</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>September 25, 2021</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>PG-13</td>\n",
-       "      <td>90 min</td>\n",
-       "      <td>Documentaries</td>\n",
-       "      <td>As her father nears the end of his life, filmm...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>s2</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Blood &amp; Water</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Ama Qamata, Khosi Ngema, Gail Mabalane, Thaban...</td>\n",
-       "      <td>South Africa</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>International TV Shows, TV Dramas, TV Mysteries</td>\n",
-       "      <td>After crossing paths at a party, a Cape Town t...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>s3</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Ganglands</td>\n",
-       "      <td>Julien Leclercq</td>\n",
-       "      <td>Sami Bouajila, Tracy Gotoas, Samuel Jouy, Nabi...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>1 Season</td>\n",
-       "      <td>Crime TV Shows, International TV Shows, TV Act...</td>\n",
-       "      <td>To protect his family from a powerful drug lor...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>s4</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Jailbirds New Orleans</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>1 Season</td>\n",
-       "      <td>Docuseries, Reality TV</td>\n",
-       "      <td>Feuds, flirtations and toilet talk go down amo...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>s5</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Kota Factory</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Mayur More, Jitendra Kumar, Ranjan Raj, Alam K...</td>\n",
-       "      <td>India</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>International TV Shows, Romantic TV Shows, TV ...</td>\n",
-       "      <td>In a city of coaching centers known to train I...</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "  show_id     type                  title         director  \\\n",
-       "0      s1    Movie   Dick Johnson Is Dead  Kirsten Johnson   \n",
-       "1      s2  TV Show          Blood & Water              NaN   \n",
-       "2      s3  TV Show              Ganglands  Julien Leclercq   \n",
-       "3      s4  TV Show  Jailbirds New Orleans              NaN   \n",
-       "4      s5  TV Show           Kota Factory              NaN   \n",
-       "\n",
-       "                                                cast        country  \\\n",
-       "0                                                NaN  United States   \n",
-       "1  Ama Qamata, Khosi Ngema, Gail Mabalane, Thaban...   South Africa   \n",
-       "2  Sami Bouajila, Tracy Gotoas, Samuel Jouy, Nabi...            NaN   \n",
-       "3                                                NaN            NaN   \n",
-       "4  Mayur More, Jitendra Kumar, Ranjan Raj, Alam K...          India   \n",
-       "\n",
-       "           date_added  release_year rating   duration  \\\n",
-       "0  September 25, 2021          2020  PG-13     90 min   \n",
-       "1  September 24, 2021          2021  TV-MA  2 Seasons   \n",
-       "2  September 24, 2021          2021  TV-MA   1 Season   \n",
-       "3  September 24, 2021          2021  TV-MA   1 Season   \n",
-       "4  September 24, 2021          2021  TV-MA  2 Seasons   \n",
-       "\n",
-       "                                           listed_in  \\\n",
-       "0                                      Documentaries   \n",
-       "1    International TV Shows, TV Dramas, TV Mysteries   \n",
-       "2  Crime TV Shows, International TV Shows, TV Act...   \n",
-       "3                             Docuseries, Reality TV   \n",
-       "4  International TV Shows, Romantic TV Shows, TV ...   \n",
-       "\n",
-       "                                         description  \n",
-       "0  As her father nears the end of his life, filmm...  \n",
-       "1  After crossing paths at a party, a Cape Town t...  \n",
-       "2  To protect his family from a powerful drug lor...  \n",
-       "3  Feuds, flirtations and toilet talk go down amo...  \n",
-       "4  In a city of coaching centers known to train I...  "
-      ]
-     },
-     "execution_count": 9,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.head()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "663ea893",
-   "metadata": {},
-   "source": [
-    "In order to access a single property of a Dataframe, we can use <b>DataFrame.property</b>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "a200e544",
-   "metadata": {},
-   "source": [
-    "To access the title of the movie/series :"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "id": "1fab5299",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0        Dick Johnson Is Dead\n",
-       "1               Blood & Water\n",
-       "2                   Ganglands\n",
-       "3       Jailbirds New Orleans\n",
-       "4                Kota Factory\n",
-       "                ...          \n",
-       "8802                   Zodiac\n",
-       "8803              Zombie Dumb\n",
-       "8804               Zombieland\n",
-       "8805                     Zoom\n",
-       "8806                   Zubaan\n",
-       "Name: title, Length: 8807, dtype: object"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.title"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "97a665d4",
-   "metadata": {},
-   "source": [
-    "An alternative is the call it like a dictionary key using indexing"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "id": "713009ed",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0        Dick Johnson Is Dead\n",
-       "1               Blood & Water\n",
-       "2                   Ganglands\n",
-       "3       Jailbirds New Orleans\n",
-       "4                Kota Factory\n",
-       "                ...          \n",
-       "8802                   Zodiac\n",
-       "8803              Zombie Dumb\n",
-       "8804               Zombieland\n",
-       "8805                     Zoom\n",
-       "8806                   Zubaan\n",
-       "Name: title, Length: 8807, dtype: object"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles['title']"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "86ab192f",
-   "metadata": {},
-   "source": [
-    "Let's try accessing the thrid title in the abpove DataFrame"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "id": "236529cb",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Ganglands'"
-      ]
-     },
-     "execution_count": 12,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles['title'][2]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 35,
-   "id": "4574d4c6",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "dtype('int64')"
-      ]
-     },
-     "execution_count": 35,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.release_year.dtype"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 36,
-   "id": "c6f13566",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0       2020.0\n",
-       "1       2021.0\n",
-       "2       2021.0\n",
-       "3       2021.0\n",
-       "4       2021.0\n",
-       "         ...  \n",
-       "8802    2007.0\n",
-       "8803    2018.0\n",
-       "8804    2009.0\n",
-       "8805    2006.0\n",
-       "8806    2015.0\n",
-       "Name: release_year, Length: 8807, dtype: float64"
-      ]
-     },
-     "execution_count": 36,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.release_year.astype('float64')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "ce081f2c",
-   "metadata": {},
-   "source": [
-    "## Indexing in Pandas"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "ac7d1fe5",
-   "metadata": {},
-   "source": [
-    "### 1)iloc - index-based selection"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "e8025399",
-   "metadata": {},
-   "source": [
-    "iloc involves selecting data based on its numerical position in data\n",
-    "\n",
-    "To select the first row of data in a DataFrame, we use:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "id": "632263ea",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "show_id                                                        s1\n",
-       "type                                                        Movie\n",
-       "title                                        Dick Johnson Is Dead\n",
-       "director                                          Kirsten Johnson\n",
-       "cast                                                          NaN\n",
-       "country                                             United States\n",
-       "date_added                                     September 25, 2021\n",
-       "release_year                                                 2020\n",
-       "rating                                                      PG-13\n",
-       "duration                                                   90 min\n",
-       "listed_in                                           Documentaries\n",
-       "description     As her father nears the end of his life, filmm...\n",
-       "Name: 0, dtype: object"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.iloc[0]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "id": "64e89cdc",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0         Movie\n",
-       "1       TV Show\n",
-       "2       TV Show\n",
-       "3       TV Show\n",
-       "4       TV Show\n",
-       "         ...   \n",
-       "8802      Movie\n",
-       "8803    TV Show\n",
-       "8804      Movie\n",
-       "8805      Movie\n",
-       "8806      Movie\n",
-       "Name: type, Length: 8807, dtype: object"
-      ]
-     },
-     "execution_count": 14,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.iloc[:,1]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "id": "341dbcd5",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>type</th>\n",
-       "      <th>title</th>\n",
-       "      <th>director</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Dick Johnson Is Dead</td>\n",
-       "      <td>Kirsten Johnson</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Blood &amp; Water</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Ganglands</td>\n",
-       "      <td>Julien Leclercq</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      type                 title         director\n",
-       "0    Movie  Dick Johnson Is Dead  Kirsten Johnson\n",
-       "1  TV Show         Blood & Water              NaN\n",
-       "2  TV Show             Ganglands  Julien Leclercq"
-      ]
-     },
-     "execution_count": 15,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.iloc[:3,[1,2,3]]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "736ceded",
-   "metadata": {},
-   "source": [
-    "### 2) loc - label-based selection"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "ceaabe23",
-   "metadata": {},
-   "source": [
-    "In this paradigm, it's the data index value, not its position, which matters.\n",
-    "\n",
-    "For example, to get the first entry in reviews, we would now do the following:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "id": "c3c6c537",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Dick Johnson Is Dead'"
-      ]
-     },
-     "execution_count": 16,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.loc[0,'title']"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "id": "1388a19a",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>title</th>\n",
-       "      <th>director</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>Dick Johnson Is Dead</td>\n",
-       "      <td>Kirsten Johnson</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>Blood &amp; Water</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>Ganglands</td>\n",
-       "      <td>Julien Leclercq</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>Jailbirds New Orleans</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>Kota Factory</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8802</th>\n",
-       "      <td>Zodiac</td>\n",
-       "      <td>David Fincher</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8803</th>\n",
-       "      <td>Zombie Dumb</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8804</th>\n",
-       "      <td>Zombieland</td>\n",
-       "      <td>Ruben Fleischer</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8805</th>\n",
-       "      <td>Zoom</td>\n",
-       "      <td>Peter Hewitt</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8806</th>\n",
-       "      <td>Zubaan</td>\n",
-       "      <td>Mozez Singh</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>8807 rows × 2 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                      title         director\n",
-       "0      Dick Johnson Is Dead  Kirsten Johnson\n",
-       "1             Blood & Water              NaN\n",
-       "2                 Ganglands  Julien Leclercq\n",
-       "3     Jailbirds New Orleans              NaN\n",
-       "4              Kota Factory              NaN\n",
-       "...                     ...              ...\n",
-       "8802                 Zodiac    David Fincher\n",
-       "8803            Zombie Dumb              NaN\n",
-       "8804             Zombieland  Ruben Fleischer\n",
-       "8805                   Zoom     Peter Hewitt\n",
-       "8806                 Zubaan      Mozez Singh\n",
-       "\n",
-       "[8807 rows x 2 columns]"
-      ]
-     },
-     "execution_count": 17,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.loc[:,['title','director']]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "9d011543",
-   "metadata": {},
-   "source": [
-    "## Conditional Selection"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "c5fe2cff",
-   "metadata": {},
-   "source": [
-    "To check which of the shows were created in the United States, we can do the following:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "id": "420cc888",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0        True\n",
-       "1       False\n",
-       "2       False\n",
-       "3       False\n",
-       "4       False\n",
-       "        ...  \n",
-       "8802     True\n",
-       "8803    False\n",
-       "8804     True\n",
-       "8805     True\n",
-       "8806    False\n",
-       "Name: country, Length: 8807, dtype: bool"
-      ]
-     },
-     "execution_count": 18,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.country == 'United States'"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "b41a1c6b",
-   "metadata": {},
-   "source": [
-    "Now to get the name and details of the shows created in the Unites States, we can do the following"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "id": "2d593f84",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>show_id</th>\n",
-       "      <th>type</th>\n",
-       "      <th>title</th>\n",
-       "      <th>director</th>\n",
-       "      <th>cast</th>\n",
-       "      <th>country</th>\n",
-       "      <th>date_added</th>\n",
-       "      <th>release_year</th>\n",
-       "      <th>rating</th>\n",
-       "      <th>duration</th>\n",
-       "      <th>listed_in</th>\n",
-       "      <th>description</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>s1</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Dick Johnson Is Dead</td>\n",
-       "      <td>Kirsten Johnson</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>September 25, 2021</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>PG-13</td>\n",
-       "      <td>90 min</td>\n",
-       "      <td>Documentaries</td>\n",
-       "      <td>As her father nears the end of his life, filmm...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>s10</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>The Starling</td>\n",
-       "      <td>Theodore Melfi</td>\n",
-       "      <td>Melissa McCarthy, Chris O'Dowd, Kevin Kline, T...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>PG-13</td>\n",
-       "      <td>104 min</td>\n",
-       "      <td>Comedies, Dramas</td>\n",
-       "      <td>A woman adjusting to life after a loss contend...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>15</th>\n",
-       "      <td>s16</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Dear White People</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Logan Browning, Brandon P. Bell, DeRon Horton,...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>September 22, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>4 Seasons</td>\n",
-       "      <td>TV Comedies, TV Dramas</td>\n",
-       "      <td>Students of color navigate the daily slights a...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>27</th>\n",
-       "      <td>s28</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Grown Ups</td>\n",
-       "      <td>Dennis Dugan</td>\n",
-       "      <td>Adam Sandler, Kevin James, Chris Rock, David S...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>September 20, 2021</td>\n",
-       "      <td>2010</td>\n",
-       "      <td>PG-13</td>\n",
-       "      <td>103 min</td>\n",
-       "      <td>Comedies</td>\n",
-       "      <td>Mourning the loss of their beloved junior high...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>28</th>\n",
-       "      <td>s29</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Dark Skies</td>\n",
-       "      <td>Scott Stewart</td>\n",
-       "      <td>Keri Russell, Josh Hamilton, J.K. Simmons, Dak...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>September 19, 2021</td>\n",
-       "      <td>2013</td>\n",
-       "      <td>PG-13</td>\n",
-       "      <td>97 min</td>\n",
-       "      <td>Horror Movies, Sci-Fi &amp; Fantasy</td>\n",
-       "      <td>A family’s idyllic suburban life shatters when...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8791</th>\n",
-       "      <td>s8792</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Young Adult</td>\n",
-       "      <td>Jason Reitman</td>\n",
-       "      <td>Charlize Theron, Patton Oswalt, Patrick Wilson...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>November 20, 2019</td>\n",
-       "      <td>2011</td>\n",
-       "      <td>R</td>\n",
-       "      <td>94 min</td>\n",
-       "      <td>Comedies, Dramas, Independent Movies</td>\n",
-       "      <td>When a divorced writer gets a letter from an o...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8793</th>\n",
-       "      <td>s8794</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Yours, Mine and Ours</td>\n",
-       "      <td>Raja Gosnell</td>\n",
-       "      <td>Dennis Quaid, Rene Russo, Sean Faris, Katija P...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>November 20, 2019</td>\n",
-       "      <td>2005</td>\n",
-       "      <td>PG</td>\n",
-       "      <td>88 min</td>\n",
-       "      <td>Children &amp; Family Movies, Comedies</td>\n",
-       "      <td>When a father of eight and a mother of 10 prep...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8802</th>\n",
-       "      <td>s8803</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zodiac</td>\n",
-       "      <td>David Fincher</td>\n",
-       "      <td>Mark Ruffalo, Jake Gyllenhaal, Robert Downey J...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>November 20, 2019</td>\n",
-       "      <td>2007</td>\n",
-       "      <td>R</td>\n",
-       "      <td>158 min</td>\n",
-       "      <td>Cult Movies, Dramas, Thrillers</td>\n",
-       "      <td>A political cartoonist, a crime reporter and a...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8804</th>\n",
-       "      <td>s8805</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zombieland</td>\n",
-       "      <td>Ruben Fleischer</td>\n",
-       "      <td>Jesse Eisenberg, Woody Harrelson, Emma Stone, ...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>November 1, 2019</td>\n",
-       "      <td>2009</td>\n",
-       "      <td>R</td>\n",
-       "      <td>88 min</td>\n",
-       "      <td>Comedies, Horror Movies</td>\n",
-       "      <td>Looking to survive in a world taken over by zo...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8805</th>\n",
-       "      <td>s8806</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zoom</td>\n",
-       "      <td>Peter Hewitt</td>\n",
-       "      <td>Tim Allen, Courteney Cox, Chevy Chase, Kate Ma...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>January 11, 2020</td>\n",
-       "      <td>2006</td>\n",
-       "      <td>PG</td>\n",
-       "      <td>88 min</td>\n",
-       "      <td>Children &amp; Family Movies, Comedies</td>\n",
-       "      <td>Dragged from civilian life, a former superhero...</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>2818 rows × 12 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     show_id     type                 title         director  \\\n",
-       "0         s1    Movie  Dick Johnson Is Dead  Kirsten Johnson   \n",
-       "9        s10    Movie          The Starling   Theodore Melfi   \n",
-       "15       s16  TV Show     Dear White People              NaN   \n",
-       "27       s28    Movie             Grown Ups     Dennis Dugan   \n",
-       "28       s29    Movie            Dark Skies    Scott Stewart   \n",
-       "...      ...      ...                   ...              ...   \n",
-       "8791   s8792    Movie           Young Adult    Jason Reitman   \n",
-       "8793   s8794    Movie  Yours, Mine and Ours     Raja Gosnell   \n",
-       "8802   s8803    Movie                Zodiac    David Fincher   \n",
-       "8804   s8805    Movie            Zombieland  Ruben Fleischer   \n",
-       "8805   s8806    Movie                  Zoom     Peter Hewitt   \n",
-       "\n",
-       "                                                   cast        country  \\\n",
-       "0                                                   NaN  United States   \n",
-       "9     Melissa McCarthy, Chris O'Dowd, Kevin Kline, T...  United States   \n",
-       "15    Logan Browning, Brandon P. Bell, DeRon Horton,...  United States   \n",
-       "27    Adam Sandler, Kevin James, Chris Rock, David S...  United States   \n",
-       "28    Keri Russell, Josh Hamilton, J.K. Simmons, Dak...  United States   \n",
-       "...                                                 ...            ...   \n",
-       "8791  Charlize Theron, Patton Oswalt, Patrick Wilson...  United States   \n",
-       "8793  Dennis Quaid, Rene Russo, Sean Faris, Katija P...  United States   \n",
-       "8802  Mark Ruffalo, Jake Gyllenhaal, Robert Downey J...  United States   \n",
-       "8804  Jesse Eisenberg, Woody Harrelson, Emma Stone, ...  United States   \n",
-       "8805  Tim Allen, Courteney Cox, Chevy Chase, Kate Ma...  United States   \n",
-       "\n",
-       "              date_added  release_year rating   duration  \\\n",
-       "0     September 25, 2021          2020  PG-13     90 min   \n",
-       "9     September 24, 2021          2021  PG-13    104 min   \n",
-       "15    September 22, 2021          2021  TV-MA  4 Seasons   \n",
-       "27    September 20, 2021          2010  PG-13    103 min   \n",
-       "28    September 19, 2021          2013  PG-13     97 min   \n",
-       "...                  ...           ...    ...        ...   \n",
-       "8791   November 20, 2019          2011      R     94 min   \n",
-       "8793   November 20, 2019          2005     PG     88 min   \n",
-       "8802   November 20, 2019          2007      R    158 min   \n",
-       "8804    November 1, 2019          2009      R     88 min   \n",
-       "8805    January 11, 2020          2006     PG     88 min   \n",
-       "\n",
-       "                                 listed_in  \\\n",
-       "0                            Documentaries   \n",
-       "9                         Comedies, Dramas   \n",
-       "15                  TV Comedies, TV Dramas   \n",
-       "27                                Comedies   \n",
-       "28         Horror Movies, Sci-Fi & Fantasy   \n",
-       "...                                    ...   \n",
-       "8791  Comedies, Dramas, Independent Movies   \n",
-       "8793    Children & Family Movies, Comedies   \n",
-       "8802        Cult Movies, Dramas, Thrillers   \n",
-       "8804               Comedies, Horror Movies   \n",
-       "8805    Children & Family Movies, Comedies   \n",
-       "\n",
-       "                                            description  \n",
-       "0     As her father nears the end of his life, filmm...  \n",
-       "9     A woman adjusting to life after a loss contend...  \n",
-       "15    Students of color navigate the daily slights a...  \n",
-       "27    Mourning the loss of their beloved junior high...  \n",
-       "28    A family’s idyllic suburban life shatters when...  \n",
-       "...                                                 ...  \n",
-       "8791  When a divorced writer gets a letter from an o...  \n",
-       "8793  When a father of eight and a mother of 10 prep...  \n",
-       "8802  A political cartoonist, a crime reporter and a...  \n",
-       "8804  Looking to survive in a world taken over by zo...  \n",
-       "8805  Dragged from civilian life, a former superhero...  \n",
-       "\n",
-       "[2818 rows x 12 columns]"
-      ]
-     },
-     "execution_count": 19,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.loc[net_titles.country==\"United States\"]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "26c54952",
-   "metadata": {},
-   "source": [
-    "Inbuilt  conditional selectors in pandas\n",
-    "- isin\n",
-    "- isnull or notnull"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "d5c1ee8b",
-   "metadata": {},
-   "source": [
-    "isin is lets you select data whose value \"is in\" a list of values. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "id": "a6a20055",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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-       "      <th></th>\n",
-       "      <th>show_id</th>\n",
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-       "      <th>0</th>\n",
-       "      <td>s1</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Dick Johnson Is Dead</td>\n",
-       "      <td>Kirsten Johnson</td>\n",
-       "      <td>NaN</td>\n",
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-       "      <td>Kota Factory</td>\n",
-       "      <td>NaN</td>\n",
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-       "      <th>9</th>\n",
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-       "      <td>The Starling</td>\n",
-       "      <td>Theodore Melfi</td>\n",
-       "      <td>Melissa McCarthy, Chris O'Dowd, Kevin Kline, T...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
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-       "      <td>A woman adjusting to life after a loss contend...</td>\n",
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-       "      <th>15</th>\n",
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-       "      <td>TV Show</td>\n",
-       "      <td>Dear White People</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Logan Browning, Brandon P. Bell, DeRon Horton,...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>September 22, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>4 Seasons</td>\n",
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-       "      <td>Students of color navigate the daily slights a...</td>\n",
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-       "    <tr>\n",
-       "      <th>24</th>\n",
-       "      <td>s25</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Jeans</td>\n",
-       "      <td>S. Shankar</td>\n",
-       "      <td>Prashanth, Aishwarya Rai Bachchan, Sri Lakshmi...</td>\n",
-       "      <td>India</td>\n",
-       "      <td>September 21, 2021</td>\n",
-       "      <td>1998</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>166 min</td>\n",
-       "      <td>Comedies, International Movies, Romantic Movies</td>\n",
-       "      <td>When the father of the man she loves insists t...</td>\n",
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-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
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-       "      <th>8799</th>\n",
-       "      <td>s8800</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zenda</td>\n",
-       "      <td>Avadhoot Gupte</td>\n",
-       "      <td>Santosh Juvekar, Siddharth Chandekar, Sachit P...</td>\n",
-       "      <td>India</td>\n",
-       "      <td>February 15, 2018</td>\n",
-       "      <td>2009</td>\n",
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-       "      <td>Dramas, International Movies</td>\n",
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-       "      <th>8802</th>\n",
-       "      <td>s8803</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zodiac</td>\n",
-       "      <td>David Fincher</td>\n",
-       "      <td>Mark Ruffalo, Jake Gyllenhaal, Robert Downey J...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>November 20, 2019</td>\n",
-       "      <td>2007</td>\n",
-       "      <td>R</td>\n",
-       "      <td>158 min</td>\n",
-       "      <td>Cult Movies, Dramas, Thrillers</td>\n",
-       "      <td>A political cartoonist, a crime reporter and a...</td>\n",
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-       "      <th>8804</th>\n",
-       "      <td>s8805</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zombieland</td>\n",
-       "      <td>Ruben Fleischer</td>\n",
-       "      <td>Jesse Eisenberg, Woody Harrelson, Emma Stone, ...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>November 1, 2019</td>\n",
-       "      <td>2009</td>\n",
-       "      <td>R</td>\n",
-       "      <td>88 min</td>\n",
-       "      <td>Comedies, Horror Movies</td>\n",
-       "      <td>Looking to survive in a world taken over by zo...</td>\n",
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-       "    <tr>\n",
-       "      <th>8805</th>\n",
-       "      <td>s8806</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zoom</td>\n",
-       "      <td>Peter Hewitt</td>\n",
-       "      <td>Tim Allen, Courteney Cox, Chevy Chase, Kate Ma...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>January 11, 2020</td>\n",
-       "      <td>2006</td>\n",
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-       "      <td>Dragged from civilian life, a former superhero...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8806</th>\n",
-       "      <td>s8807</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zubaan</td>\n",
-       "      <td>Mozez Singh</td>\n",
-       "      <td>Vicky Kaushal, Sarah-Jane Dias, Raaghav Chanan...</td>\n",
-       "      <td>India</td>\n",
-       "      <td>March 2, 2019</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>111 min</td>\n",
-       "      <td>Dramas, International Movies, Music &amp; Musicals</td>\n",
-       "      <td>A scrappy but poor boy worms his way into a ty...</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>3790 rows × 12 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     show_id     type                 title         director  \\\n",
-       "0         s1    Movie  Dick Johnson Is Dead  Kirsten Johnson   \n",
-       "4         s5  TV Show          Kota Factory              NaN   \n",
-       "9        s10    Movie          The Starling   Theodore Melfi   \n",
-       "15       s16  TV Show     Dear White People              NaN   \n",
-       "24       s25    Movie                 Jeans       S. Shankar   \n",
-       "...      ...      ...                   ...              ...   \n",
-       "8799   s8800    Movie                 Zenda   Avadhoot Gupte   \n",
-       "8802   s8803    Movie                Zodiac    David Fincher   \n",
-       "8804   s8805    Movie            Zombieland  Ruben Fleischer   \n",
-       "8805   s8806    Movie                  Zoom     Peter Hewitt   \n",
-       "8806   s8807    Movie                Zubaan      Mozez Singh   \n",
-       "\n",
-       "                                                   cast        country  \\\n",
-       "0                                                   NaN  United States   \n",
-       "4     Mayur More, Jitendra Kumar, Ranjan Raj, Alam K...          India   \n",
-       "9     Melissa McCarthy, Chris O'Dowd, Kevin Kline, T...  United States   \n",
-       "15    Logan Browning, Brandon P. Bell, DeRon Horton,...  United States   \n",
-       "24    Prashanth, Aishwarya Rai Bachchan, Sri Lakshmi...          India   \n",
-       "...                                                 ...            ...   \n",
-       "8799  Santosh Juvekar, Siddharth Chandekar, Sachit P...          India   \n",
-       "8802  Mark Ruffalo, Jake Gyllenhaal, Robert Downey J...  United States   \n",
-       "8804  Jesse Eisenberg, Woody Harrelson, Emma Stone, ...  United States   \n",
-       "8805  Tim Allen, Courteney Cox, Chevy Chase, Kate Ma...  United States   \n",
-       "8806  Vicky Kaushal, Sarah-Jane Dias, Raaghav Chanan...          India   \n",
-       "\n",
-       "              date_added  release_year rating   duration  \\\n",
-       "0     September 25, 2021          2020  PG-13     90 min   \n",
-       "4     September 24, 2021          2021  TV-MA  2 Seasons   \n",
-       "9     September 24, 2021          2021  PG-13    104 min   \n",
-       "15    September 22, 2021          2021  TV-MA  4 Seasons   \n",
-       "24    September 21, 2021          1998  TV-14    166 min   \n",
-       "...                  ...           ...    ...        ...   \n",
-       "8799   February 15, 2018          2009  TV-14    120 min   \n",
-       "8802   November 20, 2019          2007      R    158 min   \n",
-       "8804    November 1, 2019          2009      R     88 min   \n",
-       "8805    January 11, 2020          2006     PG     88 min   \n",
-       "8806       March 2, 2019          2015  TV-14    111 min   \n",
-       "\n",
-       "                                              listed_in  \\\n",
-       "0                                         Documentaries   \n",
-       "4     International TV Shows, Romantic TV Shows, TV ...   \n",
-       "9                                      Comedies, Dramas   \n",
-       "15                               TV Comedies, TV Dramas   \n",
-       "24      Comedies, International Movies, Romantic Movies   \n",
-       "...                                                 ...   \n",
-       "8799                       Dramas, International Movies   \n",
-       "8802                     Cult Movies, Dramas, Thrillers   \n",
-       "8804                            Comedies, Horror Movies   \n",
-       "8805                 Children & Family Movies, Comedies   \n",
-       "8806     Dramas, International Movies, Music & Musicals   \n",
-       "\n",
-       "                                            description  \n",
-       "0     As her father nears the end of his life, filmm...  \n",
-       "4     In a city of coaching centers known to train I...  \n",
-       "9     A woman adjusting to life after a loss contend...  \n",
-       "15    Students of color navigate the daily slights a...  \n",
-       "24    When the father of the man she loves insists t...  \n",
-       "...                                                 ...  \n",
-       "8799  A change in the leadership of a political part...  \n",
-       "8802  A political cartoonist, a crime reporter and a...  \n",
-       "8804  Looking to survive in a world taken over by zo...  \n",
-       "8805  Dragged from civilian life, a former superhero...  \n",
-       "8806  A scrappy but poor boy worms his way into a ty...  \n",
-       "\n",
-       "[3790 rows x 12 columns]"
-      ]
-     },
-     "execution_count": 20,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.loc[net_titles.country.isin(['United States', 'India'])]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "id": "60283375",
-   "metadata": {},
-   "outputs": [
-    {
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-       "      <td>2 Seasons</td>\n",
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-       "      <th>5</th>\n",
-       "      <td>s6</td>\n",
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-       "      <td>Midnight Mass</td>\n",
-       "      <td>Mike Flanagan</td>\n",
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-       "      <td>NaN</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>1 Season</td>\n",
-       "      <td>TV Dramas, TV Horror, TV Mysteries</td>\n",
-       "      <td>The arrival of a charismatic young priest brin...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>s7</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>My Little Pony: A New Generation</td>\n",
-       "      <td>Robert Cullen, José Luis Ucha</td>\n",
-       "      <td>Vanessa Hudgens, Kimiko Glenn, James Marsden, ...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>PG</td>\n",
-       "      <td>91 min</td>\n",
-       "      <td>Children &amp; Family Movies</td>\n",
-       "      <td>Equestria's divided. But a bright-eyed hero be...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8801</th>\n",
-       "      <td>s8802</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zinzana</td>\n",
-       "      <td>Majid Al Ansari</td>\n",
-       "      <td>Ali Suliman, Saleh Bakri, Yasa, Ali Al-Jabri, ...</td>\n",
-       "      <td>United Arab Emirates, Jordan</td>\n",
-       "      <td>March 9, 2016</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>96 min</td>\n",
-       "      <td>Dramas, International Movies, Thrillers</td>\n",
-       "      <td>Recovering alcoholic Talal wakes up inside a s...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8802</th>\n",
-       "      <td>s8803</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zodiac</td>\n",
-       "      <td>David Fincher</td>\n",
-       "      <td>Mark Ruffalo, Jake Gyllenhaal, Robert Downey J...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>November 20, 2019</td>\n",
-       "      <td>2007</td>\n",
-       "      <td>R</td>\n",
-       "      <td>158 min</td>\n",
-       "      <td>Cult Movies, Dramas, Thrillers</td>\n",
-       "      <td>A political cartoonist, a crime reporter and a...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8804</th>\n",
-       "      <td>s8805</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zombieland</td>\n",
-       "      <td>Ruben Fleischer</td>\n",
-       "      <td>Jesse Eisenberg, Woody Harrelson, Emma Stone, ...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>November 1, 2019</td>\n",
-       "      <td>2009</td>\n",
-       "      <td>R</td>\n",
-       "      <td>88 min</td>\n",
-       "      <td>Comedies, Horror Movies</td>\n",
-       "      <td>Looking to survive in a world taken over by zo...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8805</th>\n",
-       "      <td>s8806</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zoom</td>\n",
-       "      <td>Peter Hewitt</td>\n",
-       "      <td>Tim Allen, Courteney Cox, Chevy Chase, Kate Ma...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>January 11, 2020</td>\n",
-       "      <td>2006</td>\n",
-       "      <td>PG</td>\n",
-       "      <td>88 min</td>\n",
-       "      <td>Children &amp; Family Movies, Comedies</td>\n",
-       "      <td>Dragged from civilian life, a former superhero...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8806</th>\n",
-       "      <td>s8807</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zubaan</td>\n",
-       "      <td>Mozez Singh</td>\n",
-       "      <td>Vicky Kaushal, Sarah-Jane Dias, Raaghav Chanan...</td>\n",
-       "      <td>India</td>\n",
-       "      <td>March 2, 2019</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>111 min</td>\n",
-       "      <td>Dramas, International Movies, Music &amp; Musicals</td>\n",
-       "      <td>A scrappy but poor boy worms his way into a ty...</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>7982 rows × 12 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     show_id     type                             title  \\\n",
-       "1         s2  TV Show                     Blood & Water   \n",
-       "2         s3  TV Show                         Ganglands   \n",
-       "4         s5  TV Show                      Kota Factory   \n",
-       "5         s6  TV Show                     Midnight Mass   \n",
-       "6         s7    Movie  My Little Pony: A New Generation   \n",
-       "...      ...      ...                               ...   \n",
-       "8801   s8802    Movie                           Zinzana   \n",
-       "8802   s8803    Movie                            Zodiac   \n",
-       "8804   s8805    Movie                        Zombieland   \n",
-       "8805   s8806    Movie                              Zoom   \n",
-       "8806   s8807    Movie                            Zubaan   \n",
-       "\n",
-       "                           director  \\\n",
-       "1                               NaN   \n",
-       "2                   Julien Leclercq   \n",
-       "4                               NaN   \n",
-       "5                     Mike Flanagan   \n",
-       "6     Robert Cullen, José Luis Ucha   \n",
-       "...                             ...   \n",
-       "8801                Majid Al Ansari   \n",
-       "8802                  David Fincher   \n",
-       "8804                Ruben Fleischer   \n",
-       "8805                   Peter Hewitt   \n",
-       "8806                    Mozez Singh   \n",
-       "\n",
-       "                                                   cast  \\\n",
-       "1     Ama Qamata, Khosi Ngema, Gail Mabalane, Thaban...   \n",
-       "2     Sami Bouajila, Tracy Gotoas, Samuel Jouy, Nabi...   \n",
-       "4     Mayur More, Jitendra Kumar, Ranjan Raj, Alam K...   \n",
-       "5     Kate Siegel, Zach Gilford, Hamish Linklater, H...   \n",
-       "6     Vanessa Hudgens, Kimiko Glenn, James Marsden, ...   \n",
-       "...                                                 ...   \n",
-       "8801  Ali Suliman, Saleh Bakri, Yasa, Ali Al-Jabri, ...   \n",
-       "8802  Mark Ruffalo, Jake Gyllenhaal, Robert Downey J...   \n",
-       "8804  Jesse Eisenberg, Woody Harrelson, Emma Stone, ...   \n",
-       "8805  Tim Allen, Courteney Cox, Chevy Chase, Kate Ma...   \n",
-       "8806  Vicky Kaushal, Sarah-Jane Dias, Raaghav Chanan...   \n",
-       "\n",
-       "                           country          date_added  release_year rating  \\\n",
-       "1                     South Africa  September 24, 2021          2021  TV-MA   \n",
-       "2                              NaN  September 24, 2021          2021  TV-MA   \n",
-       "4                            India  September 24, 2021          2021  TV-MA   \n",
-       "5                              NaN  September 24, 2021          2021  TV-MA   \n",
-       "6                              NaN  September 24, 2021          2021     PG   \n",
-       "...                            ...                 ...           ...    ...   \n",
-       "8801  United Arab Emirates, Jordan       March 9, 2016          2015  TV-MA   \n",
-       "8802                 United States   November 20, 2019          2007      R   \n",
-       "8804                 United States    November 1, 2019          2009      R   \n",
-       "8805                 United States    January 11, 2020          2006     PG   \n",
-       "8806                         India       March 2, 2019          2015  TV-14   \n",
-       "\n",
-       "       duration                                          listed_in  \\\n",
-       "1     2 Seasons    International TV Shows, TV Dramas, TV Mysteries   \n",
-       "2      1 Season  Crime TV Shows, International TV Shows, TV Act...   \n",
-       "4     2 Seasons  International TV Shows, Romantic TV Shows, TV ...   \n",
-       "5      1 Season                 TV Dramas, TV Horror, TV Mysteries   \n",
-       "6        91 min                           Children & Family Movies   \n",
-       "...         ...                                                ...   \n",
-       "8801     96 min            Dramas, International Movies, Thrillers   \n",
-       "8802    158 min                     Cult Movies, Dramas, Thrillers   \n",
-       "8804     88 min                            Comedies, Horror Movies   \n",
-       "8805     88 min                 Children & Family Movies, Comedies   \n",
-       "8806    111 min     Dramas, International Movies, Music & Musicals   \n",
-       "\n",
-       "                                            description  \n",
-       "1     After crossing paths at a party, a Cape Town t...  \n",
-       "2     To protect his family from a powerful drug lor...  \n",
-       "4     In a city of coaching centers known to train I...  \n",
-       "5     The arrival of a charismatic young priest brin...  \n",
-       "6     Equestria's divided. But a bright-eyed hero be...  \n",
-       "...                                                 ...  \n",
-       "8801  Recovering alcoholic Talal wakes up inside a s...  \n",
-       "8802  A political cartoonist, a crime reporter and a...  \n",
-       "8804  Looking to survive in a world taken over by zo...  \n",
-       "8805  Dragged from civilian life, a former superhero...  \n",
-       "8806  A scrappy but poor boy worms his way into a ty...  \n",
-       "\n",
-       "[7982 rows x 12 columns]"
-      ]
-     },
-     "execution_count": 21,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.loc[net_titles.cast.notnull()]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "id": "bbd03387",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
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-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
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-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>show_id</th>\n",
-       "      <th>type</th>\n",
-       "      <th>title</th>\n",
-       "      <th>director</th>\n",
-       "      <th>cast</th>\n",
-       "      <th>country</th>\n",
-       "      <th>date_added</th>\n",
-       "      <th>release_year</th>\n",
-       "      <th>rating</th>\n",
-       "      <th>duration</th>\n",
-       "      <th>listed_in</th>\n",
-       "      <th>description</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>s1</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Dick Johnson Is Dead</td>\n",
-       "      <td>Kirsten Johnson</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>September 25, 2021</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>PG-13</td>\n",
-       "      <td>90 min</td>\n",
-       "      <td>Documentaries</td>\n",
-       "      <td>As her father nears the end of his life, filmm...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>s4</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Jailbirds New Orleans</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>1 Season</td>\n",
-       "      <td>Docuseries, Reality TV</td>\n",
-       "      <td>Feuds, flirtations and toilet talk go down amo...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>s11</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Vendetta: Truth, Lies and The Mafia</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>1 Season</td>\n",
-       "      <td>Crime TV Shows, Docuseries, International TV S...</td>\n",
-       "      <td>Sicily boasts a bold \"Anti-Mafia\" coalition. B...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>14</th>\n",
-       "      <td>s15</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Crime Stories: India Detectives</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>September 22, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>1 Season</td>\n",
-       "      <td>British TV Shows, Crime TV Shows, Docuseries</td>\n",
-       "      <td>Cameras following Bengaluru police on the job ...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>16</th>\n",
-       "      <td>s17</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Europe's Most Dangerous Man: Otto Skorzeny in ...</td>\n",
-       "      <td>Pedro de Echave García, Pablo Azorín Williams</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>September 22, 2021</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>67 min</td>\n",
-       "      <td>Documentaries, International Movies</td>\n",
-       "      <td>Declassified documents reveal the post-WWII li...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8746</th>\n",
-       "      <td>s8747</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Winnie</td>\n",
-       "      <td>Pascale Lamche</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>France, Netherlands, South Africa, Finland</td>\n",
-       "      <td>February 26, 2018</td>\n",
-       "      <td>2017</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>85 min</td>\n",
-       "      <td>Documentaries, International Movies</td>\n",
-       "      <td>Winnie Mandela speaks about her extraordinary ...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8755</th>\n",
-       "      <td>s8756</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Women Behind Bars</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>November 1, 2016</td>\n",
-       "      <td>2010</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>3 Seasons</td>\n",
-       "      <td>Crime TV Shows, Docuseries</td>\n",
-       "      <td>This reality series recounts true stories of w...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8756</th>\n",
-       "      <td>s8757</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Woodstock</td>\n",
-       "      <td>Barak Goodman</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>August 13, 2019</td>\n",
-       "      <td>2019</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>97 min</td>\n",
-       "      <td>Documentaries, Music &amp; Musicals</td>\n",
-       "      <td>For the 50th anniversary of the legendary Wood...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8763</th>\n",
-       "      <td>s8764</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>WWII: Report from the Aleutians</td>\n",
-       "      <td>John Huston</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>March 31, 2017</td>\n",
-       "      <td>1943</td>\n",
-       "      <td>TV-PG</td>\n",
-       "      <td>45 min</td>\n",
-       "      <td>Documentaries</td>\n",
-       "      <td>Filmmaker John Huston narrates this Oscar-nomi...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8803</th>\n",
-       "      <td>s8804</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Zombie Dumb</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>July 1, 2019</td>\n",
-       "      <td>2018</td>\n",
-       "      <td>TV-Y7</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>Kids' TV, Korean TV Shows, TV Comedies</td>\n",
-       "      <td>While living alone in a spooky town, a young g...</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>825 rows × 12 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     show_id     type                                              title  \\\n",
-       "0         s1    Movie                               Dick Johnson Is Dead   \n",
-       "3         s4  TV Show                              Jailbirds New Orleans   \n",
-       "10       s11  TV Show                Vendetta: Truth, Lies and The Mafia   \n",
-       "14       s15  TV Show                    Crime Stories: India Detectives   \n",
-       "16       s17    Movie  Europe's Most Dangerous Man: Otto Skorzeny in ...   \n",
-       "...      ...      ...                                                ...   \n",
-       "8746   s8747    Movie                                             Winnie   \n",
-       "8755   s8756  TV Show                                  Women Behind Bars   \n",
-       "8756   s8757    Movie                                          Woodstock   \n",
-       "8763   s8764    Movie                    WWII: Report from the Aleutians   \n",
-       "8803   s8804  TV Show                                        Zombie Dumb   \n",
-       "\n",
-       "                                           director cast  \\\n",
-       "0                                   Kirsten Johnson  NaN   \n",
-       "3                                               NaN  NaN   \n",
-       "10                                              NaN  NaN   \n",
-       "14                                              NaN  NaN   \n",
-       "16    Pedro de Echave García, Pablo Azorín Williams  NaN   \n",
-       "...                                             ...  ...   \n",
-       "8746                                 Pascale Lamche  NaN   \n",
-       "8755                                            NaN  NaN   \n",
-       "8756                                  Barak Goodman  NaN   \n",
-       "8763                                    John Huston  NaN   \n",
-       "8803                                            NaN  NaN   \n",
-       "\n",
-       "                                         country          date_added  \\\n",
-       "0                                  United States  September 25, 2021   \n",
-       "3                                            NaN  September 24, 2021   \n",
-       "10                                           NaN  September 24, 2021   \n",
-       "14                                           NaN  September 22, 2021   \n",
-       "16                                           NaN  September 22, 2021   \n",
-       "...                                          ...                 ...   \n",
-       "8746  France, Netherlands, South Africa, Finland   February 26, 2018   \n",
-       "8755                               United States    November 1, 2016   \n",
-       "8756                               United States     August 13, 2019   \n",
-       "8763                               United States      March 31, 2017   \n",
-       "8803                                         NaN        July 1, 2019   \n",
-       "\n",
-       "      release_year rating   duration  \\\n",
-       "0             2020  PG-13     90 min   \n",
-       "3             2021  TV-MA   1 Season   \n",
-       "10            2021  TV-MA   1 Season   \n",
-       "14            2021  TV-MA   1 Season   \n",
-       "16            2020  TV-MA     67 min   \n",
-       "...            ...    ...        ...   \n",
-       "8746          2017  TV-14     85 min   \n",
-       "8755          2010  TV-14  3 Seasons   \n",
-       "8756          2019  TV-MA     97 min   \n",
-       "8763          1943  TV-PG     45 min   \n",
-       "8803          2018  TV-Y7  2 Seasons   \n",
-       "\n",
-       "                                              listed_in  \\\n",
-       "0                                         Documentaries   \n",
-       "3                                Docuseries, Reality TV   \n",
-       "10    Crime TV Shows, Docuseries, International TV S...   \n",
-       "14         British TV Shows, Crime TV Shows, Docuseries   \n",
-       "16                  Documentaries, International Movies   \n",
-       "...                                                 ...   \n",
-       "8746                Documentaries, International Movies   \n",
-       "8755                         Crime TV Shows, Docuseries   \n",
-       "8756                    Documentaries, Music & Musicals   \n",
-       "8763                                      Documentaries   \n",
-       "8803             Kids' TV, Korean TV Shows, TV Comedies   \n",
-       "\n",
-       "                                            description  \n",
-       "0     As her father nears the end of his life, filmm...  \n",
-       "3     Feuds, flirtations and toilet talk go down amo...  \n",
-       "10    Sicily boasts a bold \"Anti-Mafia\" coalition. B...  \n",
-       "14    Cameras following Bengaluru police on the job ...  \n",
-       "16    Declassified documents reveal the post-WWII li...  \n",
-       "...                                                 ...  \n",
-       "8746  Winnie Mandela speaks about her extraordinary ...  \n",
-       "8755  This reality series recounts true stories of w...  \n",
-       "8756  For the 50th anniversary of the legendary Wood...  \n",
-       "8763  Filmmaker John Huston narrates this Oscar-nomi...  \n",
-       "8803  While living alone in a spooky town, a young g...  \n",
-       "\n",
-       "[825 rows x 12 columns]"
-      ]
-     },
-     "execution_count": 22,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.loc[net_titles.cast.isnull()]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "0c010421",
-   "metadata": {},
-   "source": [
-    "## Summary Functions"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "id": "83d35500",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "count      8807\n",
-       "unique        2\n",
-       "top       Movie\n",
-       "freq       6131\n",
-       "Name: type, dtype: object"
-      ]
-     },
-     "execution_count": 23,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.type.describe()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "id": "b434cfc7",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "count      8803\n",
-       "unique       17\n",
-       "top       TV-MA\n",
-       "freq       3207\n",
-       "Name: rating, dtype: object"
-      ]
-     },
-     "execution_count": 24,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.rating.describe()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
-   "id": "d736bae5",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array(['Movie', 'TV Show'], dtype=object)"
-      ]
-     },
-     "execution_count": 26,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.type.unique()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 27,
-   "id": "991b43f4",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Movie      6131\n",
-       "TV Show    2676\n",
-       "Name: type, dtype: int64"
-      ]
-     },
-     "execution_count": 27,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.type.value_counts()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "cf389b05",
-   "metadata": {},
-   "source": [
-    "## Sorting"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 28,
-   "id": "f43b4b1d",
-   "metadata": {},
-   "outputs": [
-    {
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-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>s1</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Dick Johnson Is Dead</td>\n",
-       "      <td>Kirsten Johnson</td>\n",
-       "      <td>NaN</td>\n",
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-       "      <td>September 25, 2021</td>\n",
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-       "      <td>Movie</td>\n",
-       "      <td>Under the Shadow</td>\n",
-       "      <td>Babak Anvari</td>\n",
-       "      <td>Narges Rashidi, Avin Manshadi, Bobby Naderi, R...</td>\n",
-       "      <td>United Kingdom, Jordan, Qatar, Iran</td>\n",
-       "      <td>January 7, 2017</td>\n",
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-       "      <td>Jim Gaffigan: Cinco</td>\n",
-       "      <td>Jeannie Gaffigan</td>\n",
-       "      <td>Jim Gaffigan</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>January 10, 2017</td>\n",
-       "      <td>2017</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>74 min</td>\n",
-       "      <td>Stand-Up Comedy</td>\n",
-       "      <td>America's king of clean comedy delivers wicked...</td>\n",
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-       "      <th>5638</th>\n",
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-       "      <td>Movie</td>\n",
-       "      <td>Very Big Shot</td>\n",
-       "      <td>Mir-Jean Bou Chaaya</td>\n",
-       "      <td>Alain Saadeh, Fouad Yammine, Tarek Yaacoub, Al...</td>\n",
-       "      <td>Lebanon, Qatar</td>\n",
-       "      <td>January 12, 2017</td>\n",
-       "      <td>2015</td>\n",
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-       "      <td>109 min</td>\n",
-       "      <td>Comedies, Dramas, International Movies</td>\n",
-       "      <td>When three brothers struggling to go straight ...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5637</th>\n",
-       "      <td>s5638</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Clinical</td>\n",
-       "      <td>Alistair Legrand</td>\n",
-       "      <td>Vinessa Shaw, Kevin Rahm, William Atherton, Aa...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>January 13, 2017</td>\n",
-       "      <td>2017</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>104 min</td>\n",
-       "      <td>Horror Movies, Thrillers</td>\n",
-       "      <td>A psychiatrist is plagued by flashbacks to a t...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
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-       "    <tr>\n",
-       "      <th>2406</th>\n",
-       "      <td>s2407</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Lenox Hill</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>June 10, 2020</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>1 Season</td>\n",
-       "      <td>Docuseries, Reality TV, Science &amp; Nature TV</td>\n",
-       "      <td>Four doctors at New York's storied Lenox Hill ...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5777</th>\n",
-       "      <td>s5778</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Someone Like You</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Kingone Wang, Lorene Ren, Sean Lee, Nita Lei, ...</td>\n",
-       "      <td>Taiwan</td>\n",
-       "      <td>October 1, 2016</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>1 Season</td>\n",
-       "      <td>International TV Shows, Romantic TV Shows, TV ...</td>\n",
-       "      <td>After losing his sight and his fiancee in an a...</td>\n",
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-       "    <tr>\n",
-       "      <th>2405</th>\n",
-       "      <td>s2406</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>DC's Legends of Tomorrow</td>\n",
-       "      <td>Rob Seidenglanz</td>\n",
-       "      <td>Victor Garber, Brandon Routh, Caity Lotz, Fran...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>June 10, 2020</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>5 Seasons</td>\n",
-       "      <td>TV Action &amp; Adventure, TV Sci-Fi &amp; Fantasy</td>\n",
-       "      <td>A mysterious \"time master\" from the future uni...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5730</th>\n",
-       "      <td>s5731</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Love Family</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Chris Wang, Serena Fang, Jack Lee, Amanda Chou...</td>\n",
-       "      <td>Taiwan</td>\n",
-       "      <td>November 1, 2016</td>\n",
-       "      <td>2013</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>1 Season</td>\n",
-       "      <td>International TV Shows, Romantic TV Shows, TV ...</td>\n",
-       "      <td>A wealthy heir's search for a nameless childho...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4403</th>\n",
-       "      <td>s4404</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Medal of Honor</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Oliver Hudson, Ben Schwartz, Paul Wesley, Aldi...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>November 9, 2018</td>\n",
-       "      <td>2018</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>1 Season</td>\n",
-       "      <td>Docuseries, TV Dramas</td>\n",
-       "      <td>Honoring service members whose courage merited...</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>8807 rows × 12 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     show_id     type                     title             director  \\\n",
-       "0         s1    Movie      Dick Johnson Is Dead      Kirsten Johnson   \n",
-       "5641   s5642    Movie          Under the Shadow         Babak Anvari   \n",
-       "5639   s5640    Movie       Jim Gaffigan: Cinco     Jeannie Gaffigan   \n",
-       "5638   s5639    Movie             Very Big Shot  Mir-Jean Bou Chaaya   \n",
-       "5637   s5638    Movie                  Clinical     Alistair Legrand   \n",
-       "...      ...      ...                       ...                  ...   \n",
-       "2406   s2407  TV Show                Lenox Hill                  NaN   \n",
-       "5777   s5778  TV Show          Someone Like You                  NaN   \n",
-       "2405   s2406  TV Show  DC's Legends of Tomorrow      Rob Seidenglanz   \n",
-       "5730   s5731  TV Show               Love Family                  NaN   \n",
-       "4403   s4404  TV Show            Medal of Honor                  NaN   \n",
-       "\n",
-       "                                                   cast  \\\n",
-       "0                                                   NaN   \n",
-       "5641  Narges Rashidi, Avin Manshadi, Bobby Naderi, R...   \n",
-       "5639                                       Jim Gaffigan   \n",
-       "5638  Alain Saadeh, Fouad Yammine, Tarek Yaacoub, Al...   \n",
-       "5637  Vinessa Shaw, Kevin Rahm, William Atherton, Aa...   \n",
-       "...                                                 ...   \n",
-       "2406                                                NaN   \n",
-       "5777  Kingone Wang, Lorene Ren, Sean Lee, Nita Lei, ...   \n",
-       "2405  Victor Garber, Brandon Routh, Caity Lotz, Fran...   \n",
-       "5730  Chris Wang, Serena Fang, Jack Lee, Amanda Chou...   \n",
-       "4403  Oliver Hudson, Ben Schwartz, Paul Wesley, Aldi...   \n",
-       "\n",
-       "                                  country          date_added  release_year  \\\n",
-       "0                           United States  September 25, 2021          2020   \n",
-       "5641  United Kingdom, Jordan, Qatar, Iran     January 7, 2017          2016   \n",
-       "5639                        United States    January 10, 2017          2017   \n",
-       "5638                       Lebanon, Qatar    January 12, 2017          2015   \n",
-       "5637                        United States    January 13, 2017          2017   \n",
-       "...                                   ...                 ...           ...   \n",
-       "2406                        United States       June 10, 2020          2020   \n",
-       "5777                               Taiwan     October 1, 2016          2015   \n",
-       "2405                        United States       June 10, 2020          2020   \n",
-       "5730                               Taiwan    November 1, 2016          2013   \n",
-       "4403                        United States    November 9, 2018          2018   \n",
-       "\n",
-       "     rating   duration                                          listed_in  \\\n",
-       "0     PG-13     90 min                                      Documentaries   \n",
-       "5641  PG-13     84 min     Horror Movies, International Movies, Thrillers   \n",
-       "5639  TV-14     74 min                                    Stand-Up Comedy   \n",
-       "5638  TV-MA    109 min             Comedies, Dramas, International Movies   \n",
-       "5637  TV-MA    104 min                           Horror Movies, Thrillers   \n",
-       "...     ...        ...                                                ...   \n",
-       "2406  TV-MA   1 Season        Docuseries, Reality TV, Science & Nature TV   \n",
-       "5777  TV-14   1 Season  International TV Shows, Romantic TV Shows, TV ...   \n",
-       "2405  TV-14  5 Seasons         TV Action & Adventure, TV Sci-Fi & Fantasy   \n",
-       "5730  TV-MA   1 Season  International TV Shows, Romantic TV Shows, TV ...   \n",
-       "4403  TV-MA   1 Season                              Docuseries, TV Dramas   \n",
-       "\n",
-       "                                            description  \n",
-       "0     As her father nears the end of his life, filmm...  \n",
-       "5641  During the Iran-Iraq conflict, a Tehran woman ...  \n",
-       "5639  America's king of clean comedy delivers wicked...  \n",
-       "5638  When three brothers struggling to go straight ...  \n",
-       "5637  A psychiatrist is plagued by flashbacks to a t...  \n",
-       "...                                                 ...  \n",
-       "2406  Four doctors at New York's storied Lenox Hill ...  \n",
-       "5777  After losing his sight and his fiancee in an a...  \n",
-       "2405  A mysterious \"time master\" from the future uni...  \n",
-       "5730  A wealthy heir's search for a nameless childho...  \n",
-       "4403  Honoring service members whose courage merited...  \n",
-       "\n",
-       "[8807 rows x 12 columns]"
-      ]
-     },
-     "execution_count": 28,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.sort_values(by='type')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "id": "809313ff",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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-       "    <tr>\n",
-       "      <th>693</th>\n",
-       "      <td>s694</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Ali &amp; Ratu Ratu Queens</td>\n",
-       "      <td>Lucky Kuswandi</td>\n",
-       "      <td>Iqbaal Ramadhan, Nirina Zubir, Asri Welas, Tik...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>June 17, 2021</td>\n",
-       "      <td>2021</td>\n",
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-       "    <tr>\n",
-       "      <th>781</th>\n",
-       "      <td>s782</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Black Holes | The Edge of All We Know</td>\n",
-       "      <td>Peter Galison</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>June 2, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>99 min</td>\n",
-       "      <td>Documentaries</td>\n",
-       "      <td>Follow scientists on their quest to understand...</td>\n",
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-       "    <tr>\n",
-       "      <th>762</th>\n",
-       "      <td>s763</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Sweet &amp; Sour</td>\n",
-       "      <td>Lee Kae-byeok</td>\n",
-       "      <td>Jang Ki-yong, Chae Soo-bin, Jung Soo-jung</td>\n",
-       "      <td>South Korea</td>\n",
-       "      <td>June 4, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>103 min</td>\n",
-       "      <td>Comedies, International Movies, Romantic Movies</td>\n",
-       "      <td>Faced with real-world opportunities and challe...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>763</th>\n",
-       "      <td>s764</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Sweet Tooth</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Nonso Anozie, Christian Convery, Adeel Akhtar,...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>June 4, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>1 Season</td>\n",
-       "      <td>TV Action &amp; Adventure, TV Dramas, TV Sci-Fi &amp; ...</td>\n",
-       "      <td>On a perilous adventure across a post-apocalyp...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>764</th>\n",
-       "      <td>s765</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Trippin' with the Kandasamys</td>\n",
-       "      <td>Jayan Moodley</td>\n",
-       "      <td>Jailoshini Naidoo, Maeshni Naicker, Madhushan ...</td>\n",
-       "      <td>South Africa</td>\n",
-       "      <td>June 4, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>94 min</td>\n",
-       "      <td>Comedies, International Movies, Romantic Movies</td>\n",
-       "      <td>To rekindle their marriages, best friends-turn...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8660</th>\n",
-       "      <td>s8661</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Undercover: How to Operate Behind Enemy Lines</td>\n",
-       "      <td>John Ford</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>March 31, 2017</td>\n",
-       "      <td>1943</td>\n",
-       "      <td>TV-PG</td>\n",
-       "      <td>61 min</td>\n",
-       "      <td>Classic Movies, Documentaries</td>\n",
-       "      <td>This World War II-era training film dramatizes...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8763</th>\n",
-       "      <td>s8764</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>WWII: Report from the Aleutians</td>\n",
-       "      <td>John Huston</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>March 31, 2017</td>\n",
-       "      <td>1943</td>\n",
-       "      <td>TV-PG</td>\n",
-       "      <td>45 min</td>\n",
-       "      <td>Documentaries</td>\n",
-       "      <td>Filmmaker John Huston narrates this Oscar-nomi...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8205</th>\n",
-       "      <td>s8206</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>The Battle of Midway</td>\n",
-       "      <td>John Ford</td>\n",
-       "      <td>Henry Fonda, Jane Darwell</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>March 31, 2017</td>\n",
-       "      <td>1942</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>18 min</td>\n",
-       "      <td>Classic Movies, Documentaries</td>\n",
-       "      <td>Director John Ford captures combat footage of ...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7790</th>\n",
-       "      <td>s7791</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Prelude to War</td>\n",
-       "      <td>Frank Capra</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>March 31, 2017</td>\n",
-       "      <td>1942</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>52 min</td>\n",
-       "      <td>Classic Movies, Documentaries</td>\n",
-       "      <td>Frank Capra's documentary chronicles the rise ...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4250</th>\n",
-       "      <td>s4251</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Pioneers: First Women Filmmakers*</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>December 30, 2018</td>\n",
-       "      <td>1925</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>1 Season</td>\n",
-       "      <td>TV Shows</td>\n",
-       "      <td>This collection restores films from women who ...</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>8807 rows × 12 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     show_id     type                                          title  \\\n",
-       "693     s694    Movie                         Ali & Ratu Ratu Queens   \n",
-       "781     s782    Movie          Black Holes | The Edge of All We Know   \n",
-       "762     s763    Movie                                   Sweet & Sour   \n",
-       "763     s764  TV Show                                    Sweet Tooth   \n",
-       "764     s765    Movie                   Trippin' with the Kandasamys   \n",
-       "...      ...      ...                                            ...   \n",
-       "8660   s8661    Movie  Undercover: How to Operate Behind Enemy Lines   \n",
-       "8763   s8764    Movie                WWII: Report from the Aleutians   \n",
-       "8205   s8206    Movie                           The Battle of Midway   \n",
-       "7790   s7791    Movie                                 Prelude to War   \n",
-       "4250   s4251  TV Show              Pioneers: First Women Filmmakers*   \n",
-       "\n",
-       "            director                                               cast  \\\n",
-       "693   Lucky Kuswandi  Iqbaal Ramadhan, Nirina Zubir, Asri Welas, Tik...   \n",
-       "781    Peter Galison                                                NaN   \n",
-       "762    Lee Kae-byeok          Jang Ki-yong, Chae Soo-bin, Jung Soo-jung   \n",
-       "763              NaN  Nonso Anozie, Christian Convery, Adeel Akhtar,...   \n",
-       "764    Jayan Moodley  Jailoshini Naidoo, Maeshni Naicker, Madhushan ...   \n",
-       "...              ...                                                ...   \n",
-       "8660       John Ford                                                NaN   \n",
-       "8763     John Huston                                                NaN   \n",
-       "8205       John Ford                          Henry Fonda, Jane Darwell   \n",
-       "7790     Frank Capra                                                NaN   \n",
-       "4250             NaN                                                NaN   \n",
-       "\n",
-       "            country         date_added  release_year rating  duration  \\\n",
-       "693             NaN      June 17, 2021          2021  TV-14   101 min   \n",
-       "781             NaN       June 2, 2021          2021  TV-14    99 min   \n",
-       "762     South Korea       June 4, 2021          2021  TV-14   103 min   \n",
-       "763   United States       June 4, 2021          2021  TV-14  1 Season   \n",
-       "764    South Africa       June 4, 2021          2021  TV-14    94 min   \n",
-       "...             ...                ...           ...    ...       ...   \n",
-       "8660  United States     March 31, 2017          1943  TV-PG    61 min   \n",
-       "8763  United States     March 31, 2017          1943  TV-PG    45 min   \n",
-       "8205  United States     March 31, 2017          1942  TV-14    18 min   \n",
-       "7790  United States     March 31, 2017          1942  TV-14    52 min   \n",
-       "4250            NaN  December 30, 2018          1925  TV-14  1 Season   \n",
-       "\n",
-       "                                              listed_in  \\\n",
-       "693              Comedies, Dramas, International Movies   \n",
-       "781                                       Documentaries   \n",
-       "762     Comedies, International Movies, Romantic Movies   \n",
-       "763   TV Action & Adventure, TV Dramas, TV Sci-Fi & ...   \n",
-       "764     Comedies, International Movies, Romantic Movies   \n",
-       "...                                                 ...   \n",
-       "8660                      Classic Movies, Documentaries   \n",
-       "8763                                      Documentaries   \n",
-       "8205                      Classic Movies, Documentaries   \n",
-       "7790                      Classic Movies, Documentaries   \n",
-       "4250                                           TV Shows   \n",
-       "\n",
-       "                                            description  \n",
-       "693   After his father's passing, a teenager sets ou...  \n",
-       "781   Follow scientists on their quest to understand...  \n",
-       "762   Faced with real-world opportunities and challe...  \n",
-       "763   On a perilous adventure across a post-apocalyp...  \n",
-       "764   To rekindle their marriages, best friends-turn...  \n",
-       "...                                                 ...  \n",
-       "8660  This World War II-era training film dramatizes...  \n",
-       "8763  Filmmaker John Huston narrates this Oscar-nomi...  \n",
-       "8205  Director John Ford captures combat footage of ...  \n",
-       "7790  Frank Capra's documentary chronicles the rise ...  \n",
-       "4250  This collection restores films from women who ...  \n",
-       "\n",
-       "[8807 rows x 12 columns]"
-      ]
-     },
-     "execution_count": 32,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.sort_values(by='release_year', ascending=False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 33,
-   "id": "f25a273c",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
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-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>show_id</th>\n",
-       "      <th>type</th>\n",
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-       "      <th>description</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>8423</th>\n",
-       "      <td>s8424</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>The Minimighty Kids</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>France</td>\n",
-       "      <td>April 15, 2018</td>\n",
-       "      <td>2012</td>\n",
-       "      <td>TV-G</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>Kids' TV, TV Comedies</td>\n",
-       "      <td>Some have big feet or a sniffly nose, others a...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7521</th>\n",
-       "      <td>s7522</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Mr. Young</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Brendan Meyer, Matreya Fedor, Gig Morton, Kurt...</td>\n",
-       "      <td>Canada</td>\n",
-       "      <td>April 16, 2019</td>\n",
-       "      <td>2013</td>\n",
-       "      <td>TV-G</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>Kids' TV, TV Comedies</td>\n",
-       "      <td>After Adam graduates from college at age 14, h...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7342</th>\n",
-       "      <td>s7343</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Lost Girl</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Anna Silk, Kris Holden-Ried, Ksenia Solo, Rich...</td>\n",
-       "      <td>Canada</td>\n",
-       "      <td>April 17, 2016</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>5 Seasons</td>\n",
-       "      <td>TV Dramas, TV Horror, TV Mysteries</td>\n",
-       "      <td>Discovering she's a succubus who sustains hers...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8257</th>\n",
-       "      <td>s8258</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>The Cravings</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Park Hee-bon, Phillip Choi, Hong Wan-pyo, Choi...</td>\n",
-       "      <td>South Korea</td>\n",
-       "      <td>April 20, 2017</td>\n",
-       "      <td>2016</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>International TV Shows, Korean TV Shows, TV Co...</td>\n",
-       "      <td>Thirtysomething career woman Jae-yeong attempt...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6460</th>\n",
-       "      <td>s6461</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Chewing Gum</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Michaela Coel, John Macmillan, Robert Lonsdale...</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>April 4, 2017</td>\n",
-       "      <td>2017</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>British TV Shows, International TV Shows, Roma...</td>\n",
-       "      <td>The virginal Tracey, who was raised in a stric...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6066</th>\n",
-       "      <td>s6067</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>A Young Doctor's Notebook and Other Stories</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Daniel Radcliffe, Jon Hamm, Adam Godley, Chris...</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2013</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>British TV Shows, TV Comedies, TV Dramas</td>\n",
-       "      <td>Set during the Russian Revolution, this comic ...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7847</th>\n",
-       "      <td>s7848</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Red vs. Blue</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Burnie Burns, Jason Saldaña, Gustavo Sorola, G...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>NR</td>\n",
-       "      <td>13 Seasons</td>\n",
-       "      <td>TV Action &amp; Adventure, TV Comedies, TV Sci-Fi ...</td>\n",
-       "      <td>This parody of first-person shooter games, mil...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8182</th>\n",
-       "      <td>s8183</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>The Adventures of Figaro Pho</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Luke Jurevicius, Craig Behenna, Charlotte Haml...</td>\n",
-       "      <td>Australia</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>TV-Y7</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>Kids' TV, TV Comedies</td>\n",
-       "      <td>Imagine your worst fears, then multiply them: ...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7406</th>\n",
-       "      <td>s7407</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Maron</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Marc Maron, Judd Hirsch, Josh Brener, Nora Zeh...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2016</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>4 Seasons</td>\n",
-       "      <td>TV Comedies</td>\n",
-       "      <td>Marc Maron stars as Marc Maron, who interviews...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6174</th>\n",
-       "      <td>s6175</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Anthony Bourdain: Parts Unknown</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Anthony Bourdain</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2018</td>\n",
-       "      <td>TV-PG</td>\n",
-       "      <td>5 Seasons</td>\n",
-       "      <td>Docuseries</td>\n",
-       "      <td>This CNN original series has chef Anthony Bour...</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>8807 rows × 12 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     show_id     type                                        title director  \\\n",
-       "8423   s8424  TV Show                          The Minimighty Kids      NaN   \n",
-       "7521   s7522  TV Show                                    Mr. Young      NaN   \n",
-       "7342   s7343  TV Show                                    Lost Girl      NaN   \n",
-       "8257   s8258  TV Show                                 The Cravings      NaN   \n",
-       "6460   s6461  TV Show                                  Chewing Gum      NaN   \n",
-       "...      ...      ...                                          ...      ...   \n",
-       "6066   s6067  TV Show  A Young Doctor's Notebook and Other Stories      NaN   \n",
-       "7847   s7848  TV Show                                 Red vs. Blue      NaN   \n",
-       "8182   s8183  TV Show                 The Adventures of Figaro Pho      NaN   \n",
-       "7406   s7407  TV Show                                        Maron      NaN   \n",
-       "6174   s6175  TV Show              Anthony Bourdain: Parts Unknown      NaN   \n",
-       "\n",
-       "                                                   cast         country  \\\n",
-       "8423                                                NaN          France   \n",
-       "7521  Brendan Meyer, Matreya Fedor, Gig Morton, Kurt...          Canada   \n",
-       "7342  Anna Silk, Kris Holden-Ried, Ksenia Solo, Rich...          Canada   \n",
-       "8257  Park Hee-bon, Phillip Choi, Hong Wan-pyo, Choi...     South Korea   \n",
-       "6460  Michaela Coel, John Macmillan, Robert Lonsdale...  United Kingdom   \n",
-       "...                                                 ...             ...   \n",
-       "6066  Daniel Radcliffe, Jon Hamm, Adam Godley, Chris...  United Kingdom   \n",
-       "7847  Burnie Burns, Jason Saldaña, Gustavo Sorola, G...   United States   \n",
-       "8182  Luke Jurevicius, Craig Behenna, Charlotte Haml...       Australia   \n",
-       "7406  Marc Maron, Judd Hirsch, Josh Brener, Nora Zeh...   United States   \n",
-       "6174                                   Anthony Bourdain   United States   \n",
-       "\n",
-       "           date_added  release_year rating    duration  \\\n",
-       "8423   April 15, 2018          2012   TV-G   2 Seasons   \n",
-       "7521   April 16, 2019          2013   TV-G   2 Seasons   \n",
-       "7342   April 17, 2016          2015  TV-14   5 Seasons   \n",
-       "8257   April 20, 2017          2016  TV-14   2 Seasons   \n",
-       "6460    April 4, 2017          2017  TV-MA   2 Seasons   \n",
-       "...               ...           ...    ...         ...   \n",
-       "6066              NaN          2013  TV-MA   2 Seasons   \n",
-       "7847              NaN          2015     NR  13 Seasons   \n",
-       "8182              NaN          2015  TV-Y7   2 Seasons   \n",
-       "7406              NaN          2016  TV-MA   4 Seasons   \n",
-       "6174              NaN          2018  TV-PG   5 Seasons   \n",
-       "\n",
-       "                                              listed_in  \\\n",
-       "8423                              Kids' TV, TV Comedies   \n",
-       "7521                              Kids' TV, TV Comedies   \n",
-       "7342                 TV Dramas, TV Horror, TV Mysteries   \n",
-       "8257  International TV Shows, Korean TV Shows, TV Co...   \n",
-       "6460  British TV Shows, International TV Shows, Roma...   \n",
-       "...                                                 ...   \n",
-       "6066           British TV Shows, TV Comedies, TV Dramas   \n",
-       "7847  TV Action & Adventure, TV Comedies, TV Sci-Fi ...   \n",
-       "8182                              Kids' TV, TV Comedies   \n",
-       "7406                                        TV Comedies   \n",
-       "6174                                         Docuseries   \n",
-       "\n",
-       "                                            description  \n",
-       "8423  Some have big feet or a sniffly nose, others a...  \n",
-       "7521  After Adam graduates from college at age 14, h...  \n",
-       "7342  Discovering she's a succubus who sustains hers...  \n",
-       "8257  Thirtysomething career woman Jae-yeong attempt...  \n",
-       "6460  The virginal Tracey, who was raised in a stric...  \n",
-       "...                                                 ...  \n",
-       "6066  Set during the Russian Revolution, this comic ...  \n",
-       "7847  This parody of first-person shooter games, mil...  \n",
-       "8182  Imagine your worst fears, then multiply them: ...  \n",
-       "7406  Marc Maron stars as Marc Maron, who interviews...  \n",
-       "6174  This CNN original series has chef Anthony Bour...  \n",
-       "\n",
-       "[8807 rows x 12 columns]"
-      ]
-     },
-     "execution_count": 33,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.sort_values(by=['date_added','release_year'])"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "f5054cd0",
-   "metadata": {},
-   "source": [
-    "## Missing values"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 37,
-   "id": "b8eced25",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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-       "      <th>show_id</th>\n",
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-       "      <th>title</th>\n",
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-       "      <th>description</th>\n",
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-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>6066</th>\n",
-       "      <td>s6067</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>A Young Doctor's Notebook and Other Stories</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Daniel Radcliffe, Jon Hamm, Adam Godley, Chris...</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2013</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>British TV Shows, TV Comedies, TV Dramas</td>\n",
-       "      <td>Set during the Russian Revolution, this comic ...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6174</th>\n",
-       "      <td>s6175</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Anthony Bourdain: Parts Unknown</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Anthony Bourdain</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2018</td>\n",
-       "      <td>TV-PG</td>\n",
-       "      <td>5 Seasons</td>\n",
-       "      <td>Docuseries</td>\n",
-       "      <td>This CNN original series has chef Anthony Bour...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6795</th>\n",
-       "      <td>s6796</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Frasier</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Kelsey Grammer, Jane Leeves, David Hyde Pierce...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2003</td>\n",
-       "      <td>TV-PG</td>\n",
-       "      <td>11 Seasons</td>\n",
-       "      <td>Classic &amp; Cult TV, TV Comedies</td>\n",
-       "      <td>Frasier Crane is a snooty but lovable Seattle ...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6806</th>\n",
-       "      <td>s6807</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Friends</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Jennifer Aniston, Courteney Cox, Lisa Kudrow, ...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2003</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>10 Seasons</td>\n",
-       "      <td>Classic &amp; Cult TV, TV Comedies</td>\n",
-       "      <td>This hit sitcom follows the merry misadventure...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6901</th>\n",
-       "      <td>s6902</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Gunslinger Girl</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Yuuka Nanri, Kanako Mitsuhashi, Eri Sendai, Am...</td>\n",
-       "      <td>Japan</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2008</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>Anime Series, Crime TV Shows</td>\n",
-       "      <td>On the surface, the Social Welfare Agency appe...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7196</th>\n",
-       "      <td>s7197</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Kikoriki</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Igor Dmitriev</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2010</td>\n",
-       "      <td>TV-Y</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>Kids' TV</td>\n",
-       "      <td>A wacky rabbit and his gang of animal pals hav...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7254</th>\n",
-       "      <td>s7255</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>La Familia P. Luche</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Eugenio Derbez, Consuelo Duval, Luis Manuel Áv...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2012</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>3 Seasons</td>\n",
-       "      <td>International TV Shows, Spanish-Language TV Sh...</td>\n",
-       "      <td>This irreverent sitcom featues Ludovico, Feder...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7406</th>\n",
-       "      <td>s7407</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Maron</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Marc Maron, Judd Hirsch, Josh Brener, Nora Zeh...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2016</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>4 Seasons</td>\n",
-       "      <td>TV Comedies</td>\n",
-       "      <td>Marc Maron stars as Marc Maron, who interviews...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7847</th>\n",
-       "      <td>s7848</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Red vs. Blue</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Burnie Burns, Jason Saldaña, Gustavo Sorola, G...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>NR</td>\n",
-       "      <td>13 Seasons</td>\n",
-       "      <td>TV Action &amp; Adventure, TV Comedies, TV Sci-Fi ...</td>\n",
-       "      <td>This parody of first-person shooter games, mil...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8182</th>\n",
-       "      <td>s8183</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>The Adventures of Figaro Pho</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Luke Jurevicius, Craig Behenna, Charlotte Haml...</td>\n",
-       "      <td>Australia</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>TV-Y7</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>Kids' TV, TV Comedies</td>\n",
-       "      <td>Imagine your worst fears, then multiply them: ...</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     show_id     type                                        title director  \\\n",
-       "6066   s6067  TV Show  A Young Doctor's Notebook and Other Stories      NaN   \n",
-       "6174   s6175  TV Show              Anthony Bourdain: Parts Unknown      NaN   \n",
-       "6795   s6796  TV Show                                      Frasier      NaN   \n",
-       "6806   s6807  TV Show                                      Friends      NaN   \n",
-       "6901   s6902  TV Show                              Gunslinger Girl      NaN   \n",
-       "7196   s7197  TV Show                                     Kikoriki      NaN   \n",
-       "7254   s7255  TV Show                          La Familia P. Luche      NaN   \n",
-       "7406   s7407  TV Show                                        Maron      NaN   \n",
-       "7847   s7848  TV Show                                 Red vs. Blue      NaN   \n",
-       "8182   s8183  TV Show                 The Adventures of Figaro Pho      NaN   \n",
-       "\n",
-       "                                                   cast         country  \\\n",
-       "6066  Daniel Radcliffe, Jon Hamm, Adam Godley, Chris...  United Kingdom   \n",
-       "6174                                   Anthony Bourdain   United States   \n",
-       "6795  Kelsey Grammer, Jane Leeves, David Hyde Pierce...   United States   \n",
-       "6806  Jennifer Aniston, Courteney Cox, Lisa Kudrow, ...   United States   \n",
-       "6901  Yuuka Nanri, Kanako Mitsuhashi, Eri Sendai, Am...           Japan   \n",
-       "7196                                      Igor Dmitriev             NaN   \n",
-       "7254  Eugenio Derbez, Consuelo Duval, Luis Manuel Áv...   United States   \n",
-       "7406  Marc Maron, Judd Hirsch, Josh Brener, Nora Zeh...   United States   \n",
-       "7847  Burnie Burns, Jason Saldaña, Gustavo Sorola, G...   United States   \n",
-       "8182  Luke Jurevicius, Craig Behenna, Charlotte Haml...       Australia   \n",
-       "\n",
-       "     date_added  release_year rating    duration  \\\n",
-       "6066        NaN          2013  TV-MA   2 Seasons   \n",
-       "6174        NaN          2018  TV-PG   5 Seasons   \n",
-       "6795        NaN          2003  TV-PG  11 Seasons   \n",
-       "6806        NaN          2003  TV-14  10 Seasons   \n",
-       "6901        NaN          2008  TV-14   2 Seasons   \n",
-       "7196        NaN          2010   TV-Y   2 Seasons   \n",
-       "7254        NaN          2012  TV-14   3 Seasons   \n",
-       "7406        NaN          2016  TV-MA   4 Seasons   \n",
-       "7847        NaN          2015     NR  13 Seasons   \n",
-       "8182        NaN          2015  TV-Y7   2 Seasons   \n",
-       "\n",
-       "                                              listed_in  \\\n",
-       "6066           British TV Shows, TV Comedies, TV Dramas   \n",
-       "6174                                         Docuseries   \n",
-       "6795                     Classic & Cult TV, TV Comedies   \n",
-       "6806                     Classic & Cult TV, TV Comedies   \n",
-       "6901                       Anime Series, Crime TV Shows   \n",
-       "7196                                           Kids' TV   \n",
-       "7254  International TV Shows, Spanish-Language TV Sh...   \n",
-       "7406                                        TV Comedies   \n",
-       "7847  TV Action & Adventure, TV Comedies, TV Sci-Fi ...   \n",
-       "8182                              Kids' TV, TV Comedies   \n",
-       "\n",
-       "                                            description  \n",
-       "6066  Set during the Russian Revolution, this comic ...  \n",
-       "6174  This CNN original series has chef Anthony Bour...  \n",
-       "6795  Frasier Crane is a snooty but lovable Seattle ...  \n",
-       "6806  This hit sitcom follows the merry misadventure...  \n",
-       "6901  On the surface, the Social Welfare Agency appe...  \n",
-       "7196  A wacky rabbit and his gang of animal pals hav...  \n",
-       "7254  This irreverent sitcom featues Ludovico, Feder...  \n",
-       "7406  Marc Maron stars as Marc Maron, who interviews...  \n",
-       "7847  This parody of first-person shooter games, mil...  \n",
-       "8182  Imagine your worst fears, then multiply them: ...  "
-      ]
-     },
-     "execution_count": 37,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles[pd.isnull(net_titles.date_added)]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 41,
-   "id": "6fa5ffc8",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0       September 25, 2021\n",
-       "1       September 24, 2021\n",
-       "2       September 24, 2021\n",
-       "3       September 24, 2021\n",
-       "4       September 24, 2021\n",
-       "               ...        \n",
-       "8802     November 20, 2019\n",
-       "8803          July 1, 2019\n",
-       "8804      November 1, 2019\n",
-       "8805      January 11, 2020\n",
-       "8806         March 2, 2019\n",
-       "Name: date_added, Length: 8807, dtype: object"
-      ]
-     },
-     "execution_count": 41,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.date_added.fillna('Unknown')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 42,
-   "id": "40a0a8c2",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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-       "      <th>show_id</th>\n",
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-       "      <th>6066</th>\n",
-       "      <td>s6067</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>A Young Doctor's Notebook and Other Stories</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Daniel Radcliffe, Jon Hamm, Adam Godley, Chris...</td>\n",
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-       "      <td>Set during the Russian Revolution, this comic ...</td>\n",
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-       "      <th>6174</th>\n",
-       "      <td>s6175</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Anthony Bourdain: Parts Unknown</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Anthony Bourdain</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2018</td>\n",
-       "      <td>TV-PG</td>\n",
-       "      <td>5 Seasons</td>\n",
-       "      <td>Docuseries</td>\n",
-       "      <td>This CNN original series has chef Anthony Bour...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6795</th>\n",
-       "      <td>s6796</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Frasier</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Kelsey Grammer, Jane Leeves, David Hyde Pierce...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2003</td>\n",
-       "      <td>TV-PG</td>\n",
-       "      <td>11 Seasons</td>\n",
-       "      <td>Classic &amp; Cult TV, TV Comedies</td>\n",
-       "      <td>Frasier Crane is a snooty but lovable Seattle ...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6806</th>\n",
-       "      <td>s6807</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Friends</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Jennifer Aniston, Courteney Cox, Lisa Kudrow, ...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2003</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>10 Seasons</td>\n",
-       "      <td>Classic &amp; Cult TV, TV Comedies</td>\n",
-       "      <td>This hit sitcom follows the merry misadventure...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6901</th>\n",
-       "      <td>s6902</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Gunslinger Girl</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Yuuka Nanri, Kanako Mitsuhashi, Eri Sendai, Am...</td>\n",
-       "      <td>Japan</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2008</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>Anime Series, Crime TV Shows</td>\n",
-       "      <td>On the surface, the Social Welfare Agency appe...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7196</th>\n",
-       "      <td>s7197</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Kikoriki</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Igor Dmitriev</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2010</td>\n",
-       "      <td>TV-Y</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>Kids' TV</td>\n",
-       "      <td>A wacky rabbit and his gang of animal pals hav...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7254</th>\n",
-       "      <td>s7255</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>La Familia P. Luche</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Eugenio Derbez, Consuelo Duval, Luis Manuel Áv...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2012</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>3 Seasons</td>\n",
-       "      <td>International TV Shows, Spanish-Language TV Sh...</td>\n",
-       "      <td>This irreverent sitcom featues Ludovico, Feder...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7406</th>\n",
-       "      <td>s7407</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Maron</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Marc Maron, Judd Hirsch, Josh Brener, Nora Zeh...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2016</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>4 Seasons</td>\n",
-       "      <td>TV Comedies</td>\n",
-       "      <td>Marc Maron stars as Marc Maron, who interviews...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7847</th>\n",
-       "      <td>s7848</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Red vs. Blue</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Burnie Burns, Jason Saldaña, Gustavo Sorola, G...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>NR</td>\n",
-       "      <td>13 Seasons</td>\n",
-       "      <td>TV Action &amp; Adventure, TV Comedies, TV Sci-Fi ...</td>\n",
-       "      <td>This parody of first-person shooter games, mil...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8182</th>\n",
-       "      <td>s8183</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>The Adventures of Figaro Pho</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Luke Jurevicius, Craig Behenna, Charlotte Haml...</td>\n",
-       "      <td>Australia</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>TV-Y7</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>Kids' TV, TV Comedies</td>\n",
-       "      <td>Imagine your worst fears, then multiply them: ...</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     show_id     type                                        title director  \\\n",
-       "6066   s6067  TV Show  A Young Doctor's Notebook and Other Stories      NaN   \n",
-       "6174   s6175  TV Show              Anthony Bourdain: Parts Unknown      NaN   \n",
-       "6795   s6796  TV Show                                      Frasier      NaN   \n",
-       "6806   s6807  TV Show                                      Friends      NaN   \n",
-       "6901   s6902  TV Show                              Gunslinger Girl      NaN   \n",
-       "7196   s7197  TV Show                                     Kikoriki      NaN   \n",
-       "7254   s7255  TV Show                          La Familia P. Luche      NaN   \n",
-       "7406   s7407  TV Show                                        Maron      NaN   \n",
-       "7847   s7848  TV Show                                 Red vs. Blue      NaN   \n",
-       "8182   s8183  TV Show                 The Adventures of Figaro Pho      NaN   \n",
-       "\n",
-       "                                                   cast         country  \\\n",
-       "6066  Daniel Radcliffe, Jon Hamm, Adam Godley, Chris...  United Kingdom   \n",
-       "6174                                   Anthony Bourdain   United States   \n",
-       "6795  Kelsey Grammer, Jane Leeves, David Hyde Pierce...   United States   \n",
-       "6806  Jennifer Aniston, Courteney Cox, Lisa Kudrow, ...   United States   \n",
-       "6901  Yuuka Nanri, Kanako Mitsuhashi, Eri Sendai, Am...           Japan   \n",
-       "7196                                      Igor Dmitriev             NaN   \n",
-       "7254  Eugenio Derbez, Consuelo Duval, Luis Manuel Áv...   United States   \n",
-       "7406  Marc Maron, Judd Hirsch, Josh Brener, Nora Zeh...   United States   \n",
-       "7847  Burnie Burns, Jason Saldaña, Gustavo Sorola, G...   United States   \n",
-       "8182  Luke Jurevicius, Craig Behenna, Charlotte Haml...       Australia   \n",
-       "\n",
-       "     date_added  release_year rating    duration  \\\n",
-       "6066        NaN          2013  TV-MA   2 Seasons   \n",
-       "6174        NaN          2018  TV-PG   5 Seasons   \n",
-       "6795        NaN          2003  TV-PG  11 Seasons   \n",
-       "6806        NaN          2003  TV-14  10 Seasons   \n",
-       "6901        NaN          2008  TV-14   2 Seasons   \n",
-       "7196        NaN          2010   TV-Y   2 Seasons   \n",
-       "7254        NaN          2012  TV-14   3 Seasons   \n",
-       "7406        NaN          2016  TV-MA   4 Seasons   \n",
-       "7847        NaN          2015     NR  13 Seasons   \n",
-       "8182        NaN          2015  TV-Y7   2 Seasons   \n",
-       "\n",
-       "                                              listed_in  \\\n",
-       "6066           British TV Shows, TV Comedies, TV Dramas   \n",
-       "6174                                         Docuseries   \n",
-       "6795                     Classic & Cult TV, TV Comedies   \n",
-       "6806                     Classic & Cult TV, TV Comedies   \n",
-       "6901                       Anime Series, Crime TV Shows   \n",
-       "7196                                           Kids' TV   \n",
-       "7254  International TV Shows, Spanish-Language TV Sh...   \n",
-       "7406                                        TV Comedies   \n",
-       "7847  TV Action & Adventure, TV Comedies, TV Sci-Fi ...   \n",
-       "8182                              Kids' TV, TV Comedies   \n",
-       "\n",
-       "                                            description  \n",
-       "6066  Set during the Russian Revolution, this comic ...  \n",
-       "6174  This CNN original series has chef Anthony Bour...  \n",
-       "6795  Frasier Crane is a snooty but lovable Seattle ...  \n",
-       "6806  This hit sitcom follows the merry misadventure...  \n",
-       "6901  On the surface, the Social Welfare Agency appe...  \n",
-       "7196  A wacky rabbit and his gang of animal pals hav...  \n",
-       "7254  This irreverent sitcom featues Ludovico, Feder...  \n",
-       "7406  Marc Maron stars as Marc Maron, who interviews...  \n",
-       "7847  This parody of first-person shooter games, mil...  \n",
-       "8182  Imagine your worst fears, then multiply them: ...  "
-      ]
-     },
-     "execution_count": 42,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles[pd.isnull(net_titles.date_added)]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "ac4d961e",
-   "metadata": {},
-   "source": [
-    "## Renaming and Combining of data"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "159b5c71",
-   "metadata": {},
-   "source": [
-    "### Renaming\n",
-    "The first function we'll introduce here is rename(), which lets you change index names and/or column names. For example, to change the 'duration' column in our dataset to 'no. of seasons', we would do:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 43,
-   "id": "42f1e399",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
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-       "\n",
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-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>show_id</th>\n",
-       "      <th>type</th>\n",
-       "      <th>title</th>\n",
-       "      <th>director</th>\n",
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-       "      <th>listed_in</th>\n",
-       "      <th>description</th>\n",
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-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>s1</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Dick Johnson Is Dead</td>\n",
-       "      <td>Kirsten Johnson</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>September 25, 2021</td>\n",
-       "      <td>2020</td>\n",
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-       "      <td>90 min</td>\n",
-       "      <td>Documentaries</td>\n",
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-       "      <th>1</th>\n",
-       "      <td>s2</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Blood &amp; Water</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Ama Qamata, Khosi Ngema, Gail Mabalane, Thaban...</td>\n",
-       "      <td>South Africa</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>International TV Shows, TV Dramas, TV Mysteries</td>\n",
-       "      <td>After crossing paths at a party, a Cape Town t...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>s3</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Ganglands</td>\n",
-       "      <td>Julien Leclercq</td>\n",
-       "      <td>Sami Bouajila, Tracy Gotoas, Samuel Jouy, Nabi...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>1 Season</td>\n",
-       "      <td>Crime TV Shows, International TV Shows, TV Act...</td>\n",
-       "      <td>To protect his family from a powerful drug lor...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>s4</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Jailbirds New Orleans</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>1 Season</td>\n",
-       "      <td>Docuseries, Reality TV</td>\n",
-       "      <td>Feuds, flirtations and toilet talk go down amo...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>s5</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Kota Factory</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Mayur More, Jitendra Kumar, Ranjan Raj, Alam K...</td>\n",
-       "      <td>India</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>International TV Shows, Romantic TV Shows, TV ...</td>\n",
-       "      <td>In a city of coaching centers known to train I...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8802</th>\n",
-       "      <td>s8803</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zodiac</td>\n",
-       "      <td>David Fincher</td>\n",
-       "      <td>Mark Ruffalo, Jake Gyllenhaal, Robert Downey J...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>November 20, 2019</td>\n",
-       "      <td>2007</td>\n",
-       "      <td>R</td>\n",
-       "      <td>158 min</td>\n",
-       "      <td>Cult Movies, Dramas, Thrillers</td>\n",
-       "      <td>A political cartoonist, a crime reporter and a...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8803</th>\n",
-       "      <td>s8804</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Zombie Dumb</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>July 1, 2019</td>\n",
-       "      <td>2018</td>\n",
-       "      <td>TV-Y7</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>Kids' TV, Korean TV Shows, TV Comedies</td>\n",
-       "      <td>While living alone in a spooky town, a young g...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8804</th>\n",
-       "      <td>s8805</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zombieland</td>\n",
-       "      <td>Ruben Fleischer</td>\n",
-       "      <td>Jesse Eisenberg, Woody Harrelson, Emma Stone, ...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>November 1, 2019</td>\n",
-       "      <td>2009</td>\n",
-       "      <td>R</td>\n",
-       "      <td>88 min</td>\n",
-       "      <td>Comedies, Horror Movies</td>\n",
-       "      <td>Looking to survive in a world taken over by zo...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8805</th>\n",
-       "      <td>s8806</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zoom</td>\n",
-       "      <td>Peter Hewitt</td>\n",
-       "      <td>Tim Allen, Courteney Cox, Chevy Chase, Kate Ma...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>January 11, 2020</td>\n",
-       "      <td>2006</td>\n",
-       "      <td>PG</td>\n",
-       "      <td>88 min</td>\n",
-       "      <td>Children &amp; Family Movies, Comedies</td>\n",
-       "      <td>Dragged from civilian life, a former superhero...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8806</th>\n",
-       "      <td>s8807</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zubaan</td>\n",
-       "      <td>Mozez Singh</td>\n",
-       "      <td>Vicky Kaushal, Sarah-Jane Dias, Raaghav Chanan...</td>\n",
-       "      <td>India</td>\n",
-       "      <td>March 2, 2019</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>111 min</td>\n",
-       "      <td>Dramas, International Movies, Music &amp; Musicals</td>\n",
-       "      <td>A scrappy but poor boy worms his way into a ty...</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>8807 rows × 12 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     show_id     type                  title         director  \\\n",
-       "0         s1    Movie   Dick Johnson Is Dead  Kirsten Johnson   \n",
-       "1         s2  TV Show          Blood & Water              NaN   \n",
-       "2         s3  TV Show              Ganglands  Julien Leclercq   \n",
-       "3         s4  TV Show  Jailbirds New Orleans              NaN   \n",
-       "4         s5  TV Show           Kota Factory              NaN   \n",
-       "...      ...      ...                    ...              ...   \n",
-       "8802   s8803    Movie                 Zodiac    David Fincher   \n",
-       "8803   s8804  TV Show            Zombie Dumb              NaN   \n",
-       "8804   s8805    Movie             Zombieland  Ruben Fleischer   \n",
-       "8805   s8806    Movie                   Zoom     Peter Hewitt   \n",
-       "8806   s8807    Movie                 Zubaan      Mozez Singh   \n",
-       "\n",
-       "                                                   cast        country  \\\n",
-       "0                                                   NaN  United States   \n",
-       "1     Ama Qamata, Khosi Ngema, Gail Mabalane, Thaban...   South Africa   \n",
-       "2     Sami Bouajila, Tracy Gotoas, Samuel Jouy, Nabi...            NaN   \n",
-       "3                                                   NaN            NaN   \n",
-       "4     Mayur More, Jitendra Kumar, Ranjan Raj, Alam K...          India   \n",
-       "...                                                 ...            ...   \n",
-       "8802  Mark Ruffalo, Jake Gyllenhaal, Robert Downey J...  United States   \n",
-       "8803                                                NaN            NaN   \n",
-       "8804  Jesse Eisenberg, Woody Harrelson, Emma Stone, ...  United States   \n",
-       "8805  Tim Allen, Courteney Cox, Chevy Chase, Kate Ma...  United States   \n",
-       "8806  Vicky Kaushal, Sarah-Jane Dias, Raaghav Chanan...          India   \n",
-       "\n",
-       "              date_added  release_year rating no. of seasons  \\\n",
-       "0     September 25, 2021          2020  PG-13         90 min   \n",
-       "1     September 24, 2021          2021  TV-MA      2 Seasons   \n",
-       "2     September 24, 2021          2021  TV-MA       1 Season   \n",
-       "3     September 24, 2021          2021  TV-MA       1 Season   \n",
-       "4     September 24, 2021          2021  TV-MA      2 Seasons   \n",
-       "...                  ...           ...    ...            ...   \n",
-       "8802   November 20, 2019          2007      R        158 min   \n",
-       "8803        July 1, 2019          2018  TV-Y7      2 Seasons   \n",
-       "8804    November 1, 2019          2009      R         88 min   \n",
-       "8805    January 11, 2020          2006     PG         88 min   \n",
-       "8806       March 2, 2019          2015  TV-14        111 min   \n",
-       "\n",
-       "                                              listed_in  \\\n",
-       "0                                         Documentaries   \n",
-       "1       International TV Shows, TV Dramas, TV Mysteries   \n",
-       "2     Crime TV Shows, International TV Shows, TV Act...   \n",
-       "3                                Docuseries, Reality TV   \n",
-       "4     International TV Shows, Romantic TV Shows, TV ...   \n",
-       "...                                                 ...   \n",
-       "8802                     Cult Movies, Dramas, Thrillers   \n",
-       "8803             Kids' TV, Korean TV Shows, TV Comedies   \n",
-       "8804                            Comedies, Horror Movies   \n",
-       "8805                 Children & Family Movies, Comedies   \n",
-       "8806     Dramas, International Movies, Music & Musicals   \n",
-       "\n",
-       "                                            description  \n",
-       "0     As her father nears the end of his life, filmm...  \n",
-       "1     After crossing paths at a party, a Cape Town t...  \n",
-       "2     To protect his family from a powerful drug lor...  \n",
-       "3     Feuds, flirtations and toilet talk go down amo...  \n",
-       "4     In a city of coaching centers known to train I...  \n",
-       "...                                                 ...  \n",
-       "8802  A political cartoonist, a crime reporter and a...  \n",
-       "8803  While living alone in a spooky town, a young g...  \n",
-       "8804  Looking to survive in a world taken over by zo...  \n",
-       "8805  Dragged from civilian life, a former superhero...  \n",
-       "8806  A scrappy but poor boy worms his way into a ty...  \n",
-       "\n",
-       "[8807 rows x 12 columns]"
-      ]
-     },
-     "execution_count": 43,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.rename(columns={'duration' : 'no. of seasons'})"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "d405c0a9",
-   "metadata": {},
-   "source": [
-    "<b>rename()</b> lets you rename index or column values by specifying a index or column keyword parameter, respectively. It supports a variety of input formats, but usually a Python dictionary is the most convenient. Here is an example using it to rename some elements of the index."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 44,
-   "id": "fe5d6f17",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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-       "\n",
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-       "      <th>First</th>\n",
-       "      <td>s1</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Dick Johnson Is Dead</td>\n",
-       "      <td>Kirsten Johnson</td>\n",
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-       "      <th>Second</th>\n",
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-       "      <td>NaN</td>\n",
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-       "      <th>2</th>\n",
-       "      <td>s3</td>\n",
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-       "      <td>Ganglands</td>\n",
-       "      <td>Julien Leclercq</td>\n",
-       "      <td>Sami Bouajila, Tracy Gotoas, Samuel Jouy, Nabi...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>1 Season</td>\n",
-       "      <td>Crime TV Shows, International TV Shows, TV Act...</td>\n",
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-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>s4</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Jailbirds New Orleans</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>1 Season</td>\n",
-       "      <td>Docuseries, Reality TV</td>\n",
-       "      <td>Feuds, flirtations and toilet talk go down amo...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>s5</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Kota Factory</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Mayur More, Jitendra Kumar, Ranjan Raj, Alam K...</td>\n",
-       "      <td>India</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>International TV Shows, Romantic TV Shows, TV ...</td>\n",
-       "      <td>In a city of coaching centers known to train I...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8802</th>\n",
-       "      <td>s8803</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zodiac</td>\n",
-       "      <td>David Fincher</td>\n",
-       "      <td>Mark Ruffalo, Jake Gyllenhaal, Robert Downey J...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>November 20, 2019</td>\n",
-       "      <td>2007</td>\n",
-       "      <td>R</td>\n",
-       "      <td>158 min</td>\n",
-       "      <td>Cult Movies, Dramas, Thrillers</td>\n",
-       "      <td>A political cartoonist, a crime reporter and a...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8803</th>\n",
-       "      <td>s8804</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Zombie Dumb</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>July 1, 2019</td>\n",
-       "      <td>2018</td>\n",
-       "      <td>TV-Y7</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>Kids' TV, Korean TV Shows, TV Comedies</td>\n",
-       "      <td>While living alone in a spooky town, a young g...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8804</th>\n",
-       "      <td>s8805</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zombieland</td>\n",
-       "      <td>Ruben Fleischer</td>\n",
-       "      <td>Jesse Eisenberg, Woody Harrelson, Emma Stone, ...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>November 1, 2019</td>\n",
-       "      <td>2009</td>\n",
-       "      <td>R</td>\n",
-       "      <td>88 min</td>\n",
-       "      <td>Comedies, Horror Movies</td>\n",
-       "      <td>Looking to survive in a world taken over by zo...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8805</th>\n",
-       "      <td>s8806</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zoom</td>\n",
-       "      <td>Peter Hewitt</td>\n",
-       "      <td>Tim Allen, Courteney Cox, Chevy Chase, Kate Ma...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>January 11, 2020</td>\n",
-       "      <td>2006</td>\n",
-       "      <td>PG</td>\n",
-       "      <td>88 min</td>\n",
-       "      <td>Children &amp; Family Movies, Comedies</td>\n",
-       "      <td>Dragged from civilian life, a former superhero...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8806</th>\n",
-       "      <td>s8807</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zubaan</td>\n",
-       "      <td>Mozez Singh</td>\n",
-       "      <td>Vicky Kaushal, Sarah-Jane Dias, Raaghav Chanan...</td>\n",
-       "      <td>India</td>\n",
-       "      <td>March 2, 2019</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>111 min</td>\n",
-       "      <td>Dramas, International Movies, Music &amp; Musicals</td>\n",
-       "      <td>A scrappy but poor boy worms his way into a ty...</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>8807 rows × 12 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "       show_id     type                  title         director  \\\n",
-       "First       s1    Movie   Dick Johnson Is Dead  Kirsten Johnson   \n",
-       "Second      s2  TV Show          Blood & Water              NaN   \n",
-       "2           s3  TV Show              Ganglands  Julien Leclercq   \n",
-       "3           s4  TV Show  Jailbirds New Orleans              NaN   \n",
-       "4           s5  TV Show           Kota Factory              NaN   \n",
-       "...        ...      ...                    ...              ...   \n",
-       "8802     s8803    Movie                 Zodiac    David Fincher   \n",
-       "8803     s8804  TV Show            Zombie Dumb              NaN   \n",
-       "8804     s8805    Movie             Zombieland  Ruben Fleischer   \n",
-       "8805     s8806    Movie                   Zoom     Peter Hewitt   \n",
-       "8806     s8807    Movie                 Zubaan      Mozez Singh   \n",
-       "\n",
-       "                                                     cast        country  \\\n",
-       "First                                                 NaN  United States   \n",
-       "Second  Ama Qamata, Khosi Ngema, Gail Mabalane, Thaban...   South Africa   \n",
-       "2       Sami Bouajila, Tracy Gotoas, Samuel Jouy, Nabi...            NaN   \n",
-       "3                                                     NaN            NaN   \n",
-       "4       Mayur More, Jitendra Kumar, Ranjan Raj, Alam K...          India   \n",
-       "...                                                   ...            ...   \n",
-       "8802    Mark Ruffalo, Jake Gyllenhaal, Robert Downey J...  United States   \n",
-       "8803                                                  NaN            NaN   \n",
-       "8804    Jesse Eisenberg, Woody Harrelson, Emma Stone, ...  United States   \n",
-       "8805    Tim Allen, Courteney Cox, Chevy Chase, Kate Ma...  United States   \n",
-       "8806    Vicky Kaushal, Sarah-Jane Dias, Raaghav Chanan...          India   \n",
-       "\n",
-       "                date_added  release_year rating   duration  \\\n",
-       "First   September 25, 2021          2020  PG-13     90 min   \n",
-       "Second  September 24, 2021          2021  TV-MA  2 Seasons   \n",
-       "2       September 24, 2021          2021  TV-MA   1 Season   \n",
-       "3       September 24, 2021          2021  TV-MA   1 Season   \n",
-       "4       September 24, 2021          2021  TV-MA  2 Seasons   \n",
-       "...                    ...           ...    ...        ...   \n",
-       "8802     November 20, 2019          2007      R    158 min   \n",
-       "8803          July 1, 2019          2018  TV-Y7  2 Seasons   \n",
-       "8804      November 1, 2019          2009      R     88 min   \n",
-       "8805      January 11, 2020          2006     PG     88 min   \n",
-       "8806         March 2, 2019          2015  TV-14    111 min   \n",
-       "\n",
-       "                                                listed_in  \\\n",
-       "First                                       Documentaries   \n",
-       "Second    International TV Shows, TV Dramas, TV Mysteries   \n",
-       "2       Crime TV Shows, International TV Shows, TV Act...   \n",
-       "3                                  Docuseries, Reality TV   \n",
-       "4       International TV Shows, Romantic TV Shows, TV ...   \n",
-       "...                                                   ...   \n",
-       "8802                       Cult Movies, Dramas, Thrillers   \n",
-       "8803               Kids' TV, Korean TV Shows, TV Comedies   \n",
-       "8804                              Comedies, Horror Movies   \n",
-       "8805                   Children & Family Movies, Comedies   \n",
-       "8806       Dramas, International Movies, Music & Musicals   \n",
-       "\n",
-       "                                              description  \n",
-       "First   As her father nears the end of his life, filmm...  \n",
-       "Second  After crossing paths at a party, a Cape Town t...  \n",
-       "2       To protect his family from a powerful drug lor...  \n",
-       "3       Feuds, flirtations and toilet talk go down amo...  \n",
-       "4       In a city of coaching centers known to train I...  \n",
-       "...                                                   ...  \n",
-       "8802    A political cartoonist, a crime reporter and a...  \n",
-       "8803    While living alone in a spooky town, a young g...  \n",
-       "8804    Looking to survive in a world taken over by zo...  \n",
-       "8805    Dragged from civilian life, a former superhero...  \n",
-       "8806    A scrappy but poor boy worms his way into a ty...  \n",
-       "\n",
-       "[8807 rows x 12 columns]"
-      ]
-     },
-     "execution_count": 44,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.rename(index={0 : 'First',1:'Second'})"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 45,
-   "id": "df2d635d",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
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-       "    <tr style=\"text-align: right;\">\n",
-       "      <th>fields</th>\n",
-       "      <th>show_id</th>\n",
-       "      <th>type</th>\n",
-       "      <th>title</th>\n",
-       "      <th>director</th>\n",
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-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>s1</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Dick Johnson Is Dead</td>\n",
-       "      <td>Kirsten Johnson</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>September 25, 2021</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>PG-13</td>\n",
-       "      <td>90 min</td>\n",
-       "      <td>Documentaries</td>\n",
-       "      <td>As her father nears the end of his life, filmm...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>s2</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Blood &amp; Water</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Ama Qamata, Khosi Ngema, Gail Mabalane, Thaban...</td>\n",
-       "      <td>South Africa</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>International TV Shows, TV Dramas, TV Mysteries</td>\n",
-       "      <td>After crossing paths at a party, a Cape Town t...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>s3</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Ganglands</td>\n",
-       "      <td>Julien Leclercq</td>\n",
-       "      <td>Sami Bouajila, Tracy Gotoas, Samuel Jouy, Nabi...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>1 Season</td>\n",
-       "      <td>Crime TV Shows, International TV Shows, TV Act...</td>\n",
-       "      <td>To protect his family from a powerful drug lor...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>s4</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Jailbirds New Orleans</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>1 Season</td>\n",
-       "      <td>Docuseries, Reality TV</td>\n",
-       "      <td>Feuds, flirtations and toilet talk go down amo...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>s5</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Kota Factory</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Mayur More, Jitendra Kumar, Ranjan Raj, Alam K...</td>\n",
-       "      <td>India</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>International TV Shows, Romantic TV Shows, TV ...</td>\n",
-       "      <td>In a city of coaching centers known to train I...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8802</th>\n",
-       "      <td>s8803</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zodiac</td>\n",
-       "      <td>David Fincher</td>\n",
-       "      <td>Mark Ruffalo, Jake Gyllenhaal, Robert Downey J...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>November 20, 2019</td>\n",
-       "      <td>2007</td>\n",
-       "      <td>R</td>\n",
-       "      <td>158 min</td>\n",
-       "      <td>Cult Movies, Dramas, Thrillers</td>\n",
-       "      <td>A political cartoonist, a crime reporter and a...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8803</th>\n",
-       "      <td>s8804</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Zombie Dumb</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>July 1, 2019</td>\n",
-       "      <td>2018</td>\n",
-       "      <td>TV-Y7</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>Kids' TV, Korean TV Shows, TV Comedies</td>\n",
-       "      <td>While living alone in a spooky town, a young g...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8804</th>\n",
-       "      <td>s8805</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zombieland</td>\n",
-       "      <td>Ruben Fleischer</td>\n",
-       "      <td>Jesse Eisenberg, Woody Harrelson, Emma Stone, ...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>November 1, 2019</td>\n",
-       "      <td>2009</td>\n",
-       "      <td>R</td>\n",
-       "      <td>88 min</td>\n",
-       "      <td>Comedies, Horror Movies</td>\n",
-       "      <td>Looking to survive in a world taken over by zo...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8805</th>\n",
-       "      <td>s8806</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zoom</td>\n",
-       "      <td>Peter Hewitt</td>\n",
-       "      <td>Tim Allen, Courteney Cox, Chevy Chase, Kate Ma...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>January 11, 2020</td>\n",
-       "      <td>2006</td>\n",
-       "      <td>PG</td>\n",
-       "      <td>88 min</td>\n",
-       "      <td>Children &amp; Family Movies, Comedies</td>\n",
-       "      <td>Dragged from civilian life, a former superhero...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8806</th>\n",
-       "      <td>s8807</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zubaan</td>\n",
-       "      <td>Mozez Singh</td>\n",
-       "      <td>Vicky Kaushal, Sarah-Jane Dias, Raaghav Chanan...</td>\n",
-       "      <td>India</td>\n",
-       "      <td>March 2, 2019</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>111 min</td>\n",
-       "      <td>Dramas, International Movies, Music &amp; Musicals</td>\n",
-       "      <td>A scrappy but poor boy worms his way into a ty...</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>8807 rows × 12 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "fields show_id     type                  title         director  \\\n",
-       "s.no                                                              \n",
-       "0           s1    Movie   Dick Johnson Is Dead  Kirsten Johnson   \n",
-       "1           s2  TV Show          Blood & Water              NaN   \n",
-       "2           s3  TV Show              Ganglands  Julien Leclercq   \n",
-       "3           s4  TV Show  Jailbirds New Orleans              NaN   \n",
-       "4           s5  TV Show           Kota Factory              NaN   \n",
-       "...        ...      ...                    ...              ...   \n",
-       "8802     s8803    Movie                 Zodiac    David Fincher   \n",
-       "8803     s8804  TV Show            Zombie Dumb              NaN   \n",
-       "8804     s8805    Movie             Zombieland  Ruben Fleischer   \n",
-       "8805     s8806    Movie                   Zoom     Peter Hewitt   \n",
-       "8806     s8807    Movie                 Zubaan      Mozez Singh   \n",
-       "\n",
-       "fields                                               cast        country  \\\n",
-       "s.no                                                                       \n",
-       "0                                                     NaN  United States   \n",
-       "1       Ama Qamata, Khosi Ngema, Gail Mabalane, Thaban...   South Africa   \n",
-       "2       Sami Bouajila, Tracy Gotoas, Samuel Jouy, Nabi...            NaN   \n",
-       "3                                                     NaN            NaN   \n",
-       "4       Mayur More, Jitendra Kumar, Ranjan Raj, Alam K...          India   \n",
-       "...                                                   ...            ...   \n",
-       "8802    Mark Ruffalo, Jake Gyllenhaal, Robert Downey J...  United States   \n",
-       "8803                                                  NaN            NaN   \n",
-       "8804    Jesse Eisenberg, Woody Harrelson, Emma Stone, ...  United States   \n",
-       "8805    Tim Allen, Courteney Cox, Chevy Chase, Kate Ma...  United States   \n",
-       "8806    Vicky Kaushal, Sarah-Jane Dias, Raaghav Chanan...          India   \n",
-       "\n",
-       "fields          date_added  release_year rating   duration  \\\n",
-       "s.no                                                         \n",
-       "0       September 25, 2021          2020  PG-13     90 min   \n",
-       "1       September 24, 2021          2021  TV-MA  2 Seasons   \n",
-       "2       September 24, 2021          2021  TV-MA   1 Season   \n",
-       "3       September 24, 2021          2021  TV-MA   1 Season   \n",
-       "4       September 24, 2021          2021  TV-MA  2 Seasons   \n",
-       "...                    ...           ...    ...        ...   \n",
-       "8802     November 20, 2019          2007      R    158 min   \n",
-       "8803          July 1, 2019          2018  TV-Y7  2 Seasons   \n",
-       "8804      November 1, 2019          2009      R     88 min   \n",
-       "8805      January 11, 2020          2006     PG     88 min   \n",
-       "8806         March 2, 2019          2015  TV-14    111 min   \n",
-       "\n",
-       "fields                                          listed_in  \\\n",
-       "s.no                                                        \n",
-       "0                                           Documentaries   \n",
-       "1         International TV Shows, TV Dramas, TV Mysteries   \n",
-       "2       Crime TV Shows, International TV Shows, TV Act...   \n",
-       "3                                  Docuseries, Reality TV   \n",
-       "4       International TV Shows, Romantic TV Shows, TV ...   \n",
-       "...                                                   ...   \n",
-       "8802                       Cult Movies, Dramas, Thrillers   \n",
-       "8803               Kids' TV, Korean TV Shows, TV Comedies   \n",
-       "8804                              Comedies, Horror Movies   \n",
-       "8805                   Children & Family Movies, Comedies   \n",
-       "8806       Dramas, International Movies, Music & Musicals   \n",
-       "\n",
-       "fields                                        description  \n",
-       "s.no                                                       \n",
-       "0       As her father nears the end of his life, filmm...  \n",
-       "1       After crossing paths at a party, a Cape Town t...  \n",
-       "2       To protect his family from a powerful drug lor...  \n",
-       "3       Feuds, flirtations and toilet talk go down amo...  \n",
-       "4       In a city of coaching centers known to train I...  \n",
-       "...                                                   ...  \n",
-       "8802    A political cartoonist, a crime reporter and a...  \n",
-       "8803    While living alone in a spooky town, a young g...  \n",
-       "8804    Looking to survive in a world taken over by zo...  \n",
-       "8805    Dragged from civilian life, a former superhero...  \n",
-       "8806    A scrappy but poor boy worms his way into a ty...  \n",
-       "\n",
-       "[8807 rows x 12 columns]"
-      ]
-     },
-     "execution_count": 45,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.rename_axis('s.no',axis='rows').rename_axis('fields',axis='columns')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "6857aeca",
-   "metadata": {},
-   "source": [
-    "### Combining datasets"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "49e4c6f6",
-   "metadata": {},
-   "source": [
-    "### concat( )"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 48,
-   "id": "acad14e4",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "net_top10=pd.read_csv(\"netflix daily top 10.csv\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 50,
-   "id": "344a55cb",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>As of</th>\n",
-       "      <th>Rank</th>\n",
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-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>2020-04-01</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>Tiger King: Murder, Mayhem …</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Mar 20, 2020</td>\n",
-       "      <td>9</td>\n",
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-       "      <th>1</th>\n",
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-       "      <td>2</td>\n",
-       "      <td>2</td>\n",
-       "      <td>-</td>\n",
-       "      <td>Ozark</td>\n",
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-       "      <td>3</td>\n",
-       "      <td>3</td>\n",
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-       "      <td>All American</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Mar 28, 2019</td>\n",
-       "      <td>9</td>\n",
-       "      <td>76</td>\n",
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-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>2020-04-01</td>\n",
-       "      <td>4</td>\n",
-       "      <td>4</td>\n",
-       "      <td>-</td>\n",
-       "      <td>Blood Father</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Mar 26, 2020</td>\n",
-       "      <td>5</td>\n",
-       "      <td>30</td>\n",
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-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>2020-04-01</td>\n",
-       "      <td>5</td>\n",
-       "      <td>5</td>\n",
-       "      <td>4</td>\n",
-       "      <td>The Platform</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Mar 20, 2020</td>\n",
-       "      <td>9</td>\n",
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-       "      <td>...</td>\n",
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-       "    <tr>\n",
-       "      <th>7095</th>\n",
-       "      <td>2022-03-11</td>\n",
-       "      <td>6</td>\n",
-       "      <td>5</td>\n",
-       "      <td>1</td>\n",
-       "      <td>Worst Roommate Ever</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Mar 1, 2022</td>\n",
-       "      <td>10</td>\n",
-       "      <td>81</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7096</th>\n",
-       "      <td>2022-03-11</td>\n",
-       "      <td>7</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2</td>\n",
-       "      <td>Vikings: Valhalla</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Feb 25, 2022</td>\n",
-       "      <td>14</td>\n",
-       "      <td>100</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7097</th>\n",
-       "      <td>2022-03-11</td>\n",
-       "      <td>8</td>\n",
-       "      <td>8</td>\n",
-       "      <td>-</td>\n",
-       "      <td>Shooter</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Aug 1, 2014</td>\n",
-       "      <td>3</td>\n",
-       "      <td>7</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7098</th>\n",
-       "      <td>2022-03-11</td>\n",
-       "      <td>9</td>\n",
-       "      <td>9</td>\n",
-       "      <td>7</td>\n",
-       "      <td>Shrek 2</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Mar 1, 2022</td>\n",
-       "      <td>10</td>\n",
-       "      <td>33</td>\n",
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-       "      <th>7099</th>\n",
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-       "      <td>-</td>\n",
-       "      <td>Shrek</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>May 1, 2018</td>\n",
-       "      <td>7</td>\n",
-       "      <td>12</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>7100 rows × 10 columns</p>\n",
-       "</div>"
-      ],
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-       "           As of  Rank Year to Date Rank Last Week Rank  \\\n",
-       "0     2020-04-01     1                 1              1   \n",
-       "1     2020-04-01     2                 2              -   \n",
-       "2     2020-04-01     3                 3              2   \n",
-       "3     2020-04-01     4                 4              -   \n",
-       "4     2020-04-01     5                 5              4   \n",
-       "...          ...   ...               ...            ...   \n",
-       "7095  2022-03-11     6                 5              1   \n",
-       "7096  2022-03-11     7                 7              2   \n",
-       "7097  2022-03-11     8                 8              -   \n",
-       "7098  2022-03-11     9                 9              7   \n",
-       "7099  2022-03-11    10                10              -   \n",
-       "\n",
-       "                             Title     Type Netflix Exclusive  \\\n",
-       "0     Tiger King: Murder, Mayhem …  TV Show               Yes   \n",
-       "1                            Ozark  TV Show               Yes   \n",
-       "2                     All American  TV Show               NaN   \n",
-       "3                     Blood Father    Movie               NaN   \n",
-       "4                     The Platform    Movie               Yes   \n",
-       "...                            ...      ...               ...   \n",
-       "7095           Worst Roommate Ever  TV Show               Yes   \n",
-       "7096             Vikings: Valhalla  TV Show               Yes   \n",
-       "7097                       Shooter    Movie               NaN   \n",
-       "7098                       Shrek 2    Movie               NaN   \n",
-       "7099                         Shrek    Movie               NaN   \n",
-       "\n",
-       "     Netflix Release Date  Days In Top 10  Viewership Score  \n",
-       "0            Mar 20, 2020               9                90  \n",
-       "1            Jul 21, 2017               5                45  \n",
-       "2            Mar 28, 2019               9                76  \n",
-       "3            Mar 26, 2020               5                30  \n",
-       "4            Mar 20, 2020               9                55  \n",
-       "...                   ...             ...               ...  \n",
-       "7095          Mar 1, 2022              10                81  \n",
-       "7096         Feb 25, 2022              14               100  \n",
-       "7097          Aug 1, 2014               3                 7  \n",
-       "7098          Mar 1, 2022              10                33  \n",
-       "7099          May 1, 2018               7                12  \n",
-       "\n",
-       "[7100 rows x 10 columns]"
-      ]
-     },
-     "execution_count": 50,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_top10"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 51,
-   "id": "345a2c18",
-   "metadata": {},
-   "outputs": [
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-       "      <td>South Africa</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021.0</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>...</td>\n",
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-       "      <td>NaN</td>\n",
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-       "      <td>Ganglands</td>\n",
-       "      <td>Julien Leclercq</td>\n",
-       "      <td>Sami Bouajila, Tracy Gotoas, Samuel Jouy, Nabi...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021.0</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>1 Season</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
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-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>s4</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Jailbirds New Orleans</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021.0</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>1 Season</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>s5</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Kota Factory</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Mayur More, Jitendra Kumar, Ranjan Raj, Alam K...</td>\n",
-       "      <td>India</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021.0</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
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-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>2022-03-11</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>5</td>\n",
-       "      <td>1</td>\n",
-       "      <td>Worst Roommate Ever</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Mar 1, 2022</td>\n",
-       "      <td>10.0</td>\n",
-       "      <td>81.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7096</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
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-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>2022-03-11</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2</td>\n",
-       "      <td>Vikings: Valhalla</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Feb 25, 2022</td>\n",
-       "      <td>14.0</td>\n",
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-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>2022-03-11</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>8</td>\n",
-       "      <td>-</td>\n",
-       "      <td>Shooter</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Aug 1, 2014</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>7.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7098</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>2022-03-11</td>\n",
-       "      <td>9.0</td>\n",
-       "      <td>9</td>\n",
-       "      <td>7</td>\n",
-       "      <td>Shrek 2</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Mar 1, 2022</td>\n",
-       "      <td>10.0</td>\n",
-       "      <td>33.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7099</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>2022-03-11</td>\n",
-       "      <td>10.0</td>\n",
-       "      <td>10</td>\n",
-       "      <td>-</td>\n",
-       "      <td>Shrek</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>May 1, 2018</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>12.0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>15907 rows × 22 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     show_id     type                  title         director  \\\n",
-       "0         s1    Movie   Dick Johnson Is Dead  Kirsten Johnson   \n",
-       "1         s2  TV Show          Blood & Water              NaN   \n",
-       "2         s3  TV Show              Ganglands  Julien Leclercq   \n",
-       "3         s4  TV Show  Jailbirds New Orleans              NaN   \n",
-       "4         s5  TV Show           Kota Factory              NaN   \n",
-       "...      ...      ...                    ...              ...   \n",
-       "7095     NaN      NaN                    NaN              NaN   \n",
-       "7096     NaN      NaN                    NaN              NaN   \n",
-       "7097     NaN      NaN                    NaN              NaN   \n",
-       "7098     NaN      NaN                    NaN              NaN   \n",
-       "7099     NaN      NaN                    NaN              NaN   \n",
-       "\n",
-       "                                                   cast        country  \\\n",
-       "0                                                   NaN  United States   \n",
-       "1     Ama Qamata, Khosi Ngema, Gail Mabalane, Thaban...   South Africa   \n",
-       "2     Sami Bouajila, Tracy Gotoas, Samuel Jouy, Nabi...            NaN   \n",
-       "3                                                   NaN            NaN   \n",
-       "4     Mayur More, Jitendra Kumar, Ranjan Raj, Alam K...          India   \n",
-       "...                                                 ...            ...   \n",
-       "7095                                                NaN            NaN   \n",
-       "7096                                                NaN            NaN   \n",
-       "7097                                                NaN            NaN   \n",
-       "7098                                                NaN            NaN   \n",
-       "7099                                                NaN            NaN   \n",
-       "\n",
-       "              date_added  release_year rating   duration  ...       As of  \\\n",
-       "0     September 25, 2021        2020.0  PG-13     90 min  ...         NaN   \n",
-       "1     September 24, 2021        2021.0  TV-MA  2 Seasons  ...         NaN   \n",
-       "2     September 24, 2021        2021.0  TV-MA   1 Season  ...         NaN   \n",
-       "3     September 24, 2021        2021.0  TV-MA   1 Season  ...         NaN   \n",
-       "4     September 24, 2021        2021.0  TV-MA  2 Seasons  ...         NaN   \n",
-       "...                  ...           ...    ...        ...  ...         ...   \n",
-       "7095                 NaN           NaN    NaN        NaN  ...  2022-03-11   \n",
-       "7096                 NaN           NaN    NaN        NaN  ...  2022-03-11   \n",
-       "7097                 NaN           NaN    NaN        NaN  ...  2022-03-11   \n",
-       "7098                 NaN           NaN    NaN        NaN  ...  2022-03-11   \n",
-       "7099                 NaN           NaN    NaN        NaN  ...  2022-03-11   \n",
-       "\n",
-       "      Rank Year to Date Rank  Last Week Rank                Title     Type  \\\n",
-       "0      NaN               NaN             NaN                  NaN      NaN   \n",
-       "1      NaN               NaN             NaN                  NaN      NaN   \n",
-       "2      NaN               NaN             NaN                  NaN      NaN   \n",
-       "3      NaN               NaN             NaN                  NaN      NaN   \n",
-       "4      NaN               NaN             NaN                  NaN      NaN   \n",
-       "...    ...               ...             ...                  ...      ...   \n",
-       "7095   6.0                 5               1  Worst Roommate Ever  TV Show   \n",
-       "7096   7.0                 7               2    Vikings: Valhalla  TV Show   \n",
-       "7097   8.0                 8               -              Shooter    Movie   \n",
-       "7098   9.0                 9               7              Shrek 2    Movie   \n",
-       "7099  10.0                10               -                Shrek    Movie   \n",
-       "\n",
-       "     Netflix Exclusive Netflix Release Date Days In Top 10 Viewership Score  \n",
-       "0                  NaN                  NaN            NaN              NaN  \n",
-       "1                  NaN                  NaN            NaN              NaN  \n",
-       "2                  NaN                  NaN            NaN              NaN  \n",
-       "3                  NaN                  NaN            NaN              NaN  \n",
-       "4                  NaN                  NaN            NaN              NaN  \n",
-       "...                ...                  ...            ...              ...  \n",
-       "7095               Yes          Mar 1, 2022           10.0             81.0  \n",
-       "7096               Yes         Feb 25, 2022           14.0            100.0  \n",
-       "7097               NaN          Aug 1, 2014            3.0              7.0  \n",
-       "7098               NaN          Mar 1, 2022           10.0             33.0  \n",
-       "7099               NaN          May 1, 2018            7.0             12.0  \n",
-       "\n",
-       "[15907 rows x 22 columns]"
-      ]
-     },
-     "execution_count": 51,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "pd.concat([net_titles,net_top10])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 54,
-   "id": "df66aef0",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>show_id</th>\n",
-       "      <th>type</th>\n",
-       "      <th>title</th>\n",
-       "      <th>director</th>\n",
-       "      <th>cast</th>\n",
-       "      <th>country</th>\n",
-       "      <th>date_added</th>\n",
-       "      <th>release_year</th>\n",
-       "      <th>rating</th>\n",
-       "      <th>duration</th>\n",
-       "      <th>...</th>\n",
-       "      <th>As of</th>\n",
-       "      <th>Rank</th>\n",
-       "      <th>Year to Date Rank</th>\n",
-       "      <th>Last Week Rank</th>\n",
-       "      <th>Title</th>\n",
-       "      <th>Type</th>\n",
-       "      <th>Netflix Exclusive</th>\n",
-       "      <th>Netflix Release Date</th>\n",
-       "      <th>Days In Top 10</th>\n",
-       "      <th>Viewership Score</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>s1</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Dick Johnson Is Dead</td>\n",
-       "      <td>Kirsten Johnson</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>September 25, 2021</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>PG-13</td>\n",
-       "      <td>90 min</td>\n",
-       "      <td>...</td>\n",
-       "      <td>2020-04-01</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>Tiger King: Murder, Mayhem …</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Mar 20, 2020</td>\n",
-       "      <td>9.0</td>\n",
-       "      <td>90.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>s2</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Blood &amp; Water</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Ama Qamata, Khosi Ngema, Gail Mabalane, Thaban...</td>\n",
-       "      <td>South Africa</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>...</td>\n",
-       "      <td>2020-04-01</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2</td>\n",
-       "      <td>-</td>\n",
-       "      <td>Ozark</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Jul 21, 2017</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>45.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>s3</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Ganglands</td>\n",
-       "      <td>Julien Leclercq</td>\n",
-       "      <td>Sami Bouajila, Tracy Gotoas, Samuel Jouy, Nabi...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>1 Season</td>\n",
-       "      <td>...</td>\n",
-       "      <td>2020-04-01</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3</td>\n",
-       "      <td>2</td>\n",
-       "      <td>All American</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Mar 28, 2019</td>\n",
-       "      <td>9.0</td>\n",
-       "      <td>76.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>s4</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Jailbirds New Orleans</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>1 Season</td>\n",
-       "      <td>...</td>\n",
-       "      <td>2020-04-01</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4</td>\n",
-       "      <td>-</td>\n",
-       "      <td>Blood Father</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Mar 26, 2020</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>30.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>s5</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Kota Factory</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Mayur More, Jitendra Kumar, Ranjan Raj, Alam K...</td>\n",
-       "      <td>India</td>\n",
-       "      <td>September 24, 2021</td>\n",
-       "      <td>2021</td>\n",
-       "      <td>TV-MA</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>...</td>\n",
-       "      <td>2020-04-01</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>5</td>\n",
-       "      <td>4</td>\n",
-       "      <td>The Platform</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Mar 20, 2020</td>\n",
-       "      <td>9.0</td>\n",
-       "      <td>55.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8802</th>\n",
-       "      <td>s8803</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zodiac</td>\n",
-       "      <td>David Fincher</td>\n",
-       "      <td>Mark Ruffalo, Jake Gyllenhaal, Robert Downey J...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>November 20, 2019</td>\n",
-       "      <td>2007</td>\n",
-       "      <td>R</td>\n",
-       "      <td>158 min</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8803</th>\n",
-       "      <td>s8804</td>\n",
-       "      <td>TV Show</td>\n",
-       "      <td>Zombie Dumb</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>July 1, 2019</td>\n",
-       "      <td>2018</td>\n",
-       "      <td>TV-Y7</td>\n",
-       "      <td>2 Seasons</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8804</th>\n",
-       "      <td>s8805</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zombieland</td>\n",
-       "      <td>Ruben Fleischer</td>\n",
-       "      <td>Jesse Eisenberg, Woody Harrelson, Emma Stone, ...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>November 1, 2019</td>\n",
-       "      <td>2009</td>\n",
-       "      <td>R</td>\n",
-       "      <td>88 min</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8805</th>\n",
-       "      <td>s8806</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zoom</td>\n",
-       "      <td>Peter Hewitt</td>\n",
-       "      <td>Tim Allen, Courteney Cox, Chevy Chase, Kate Ma...</td>\n",
-       "      <td>United States</td>\n",
-       "      <td>January 11, 2020</td>\n",
-       "      <td>2006</td>\n",
-       "      <td>PG</td>\n",
-       "      <td>88 min</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8806</th>\n",
-       "      <td>s8807</td>\n",
-       "      <td>Movie</td>\n",
-       "      <td>Zubaan</td>\n",
-       "      <td>Mozez Singh</td>\n",
-       "      <td>Vicky Kaushal, Sarah-Jane Dias, Raaghav Chanan...</td>\n",
-       "      <td>India</td>\n",
-       "      <td>March 2, 2019</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>TV-14</td>\n",
-       "      <td>111 min</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>8807 rows × 22 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     show_id     type                  title         director  \\\n",
-       "0         s1    Movie   Dick Johnson Is Dead  Kirsten Johnson   \n",
-       "1         s2  TV Show          Blood & Water              NaN   \n",
-       "2         s3  TV Show              Ganglands  Julien Leclercq   \n",
-       "3         s4  TV Show  Jailbirds New Orleans              NaN   \n",
-       "4         s5  TV Show           Kota Factory              NaN   \n",
-       "...      ...      ...                    ...              ...   \n",
-       "8802   s8803    Movie                 Zodiac    David Fincher   \n",
-       "8803   s8804  TV Show            Zombie Dumb              NaN   \n",
-       "8804   s8805    Movie             Zombieland  Ruben Fleischer   \n",
-       "8805   s8806    Movie                   Zoom     Peter Hewitt   \n",
-       "8806   s8807    Movie                 Zubaan      Mozez Singh   \n",
-       "\n",
-       "                                                   cast        country  \\\n",
-       "0                                                   NaN  United States   \n",
-       "1     Ama Qamata, Khosi Ngema, Gail Mabalane, Thaban...   South Africa   \n",
-       "2     Sami Bouajila, Tracy Gotoas, Samuel Jouy, Nabi...            NaN   \n",
-       "3                                                   NaN            NaN   \n",
-       "4     Mayur More, Jitendra Kumar, Ranjan Raj, Alam K...          India   \n",
-       "...                                                 ...            ...   \n",
-       "8802  Mark Ruffalo, Jake Gyllenhaal, Robert Downey J...  United States   \n",
-       "8803                                                NaN            NaN   \n",
-       "8804  Jesse Eisenberg, Woody Harrelson, Emma Stone, ...  United States   \n",
-       "8805  Tim Allen, Courteney Cox, Chevy Chase, Kate Ma...  United States   \n",
-       "8806  Vicky Kaushal, Sarah-Jane Dias, Raaghav Chanan...          India   \n",
-       "\n",
-       "              date_added  release_year rating   duration  ...       As of  \\\n",
-       "0     September 25, 2021          2020  PG-13     90 min  ...  2020-04-01   \n",
-       "1     September 24, 2021          2021  TV-MA  2 Seasons  ...  2020-04-01   \n",
-       "2     September 24, 2021          2021  TV-MA   1 Season  ...  2020-04-01   \n",
-       "3     September 24, 2021          2021  TV-MA   1 Season  ...  2020-04-01   \n",
-       "4     September 24, 2021          2021  TV-MA  2 Seasons  ...  2020-04-01   \n",
-       "...                  ...           ...    ...        ...  ...         ...   \n",
-       "8802   November 20, 2019          2007      R    158 min  ...         NaN   \n",
-       "8803        July 1, 2019          2018  TV-Y7  2 Seasons  ...         NaN   \n",
-       "8804    November 1, 2019          2009      R     88 min  ...         NaN   \n",
-       "8805    January 11, 2020          2006     PG     88 min  ...         NaN   \n",
-       "8806       March 2, 2019          2015  TV-14    111 min  ...         NaN   \n",
-       "\n",
-       "     Rank Year to Date Rank  Last Week Rank                         Title  \\\n",
-       "0     1.0                 1               1  Tiger King: Murder, Mayhem …   \n",
-       "1     2.0                 2               -                         Ozark   \n",
-       "2     3.0                 3               2                  All American   \n",
-       "3     4.0                 4               -                  Blood Father   \n",
-       "4     5.0                 5               4                  The Platform   \n",
-       "...   ...               ...             ...                           ...   \n",
-       "8802  NaN               NaN             NaN                           NaN   \n",
-       "8803  NaN               NaN             NaN                           NaN   \n",
-       "8804  NaN               NaN             NaN                           NaN   \n",
-       "8805  NaN               NaN             NaN                           NaN   \n",
-       "8806  NaN               NaN             NaN                           NaN   \n",
-       "\n",
-       "         Type Netflix Exclusive Netflix Release Date Days In Top 10  \\\n",
-       "0     TV Show               Yes         Mar 20, 2020            9.0   \n",
-       "1     TV Show               Yes         Jul 21, 2017            5.0   \n",
-       "2     TV Show               NaN         Mar 28, 2019            9.0   \n",
-       "3       Movie               NaN         Mar 26, 2020            5.0   \n",
-       "4       Movie               Yes         Mar 20, 2020            9.0   \n",
-       "...       ...               ...                  ...            ...   \n",
-       "8802      NaN               NaN                  NaN            NaN   \n",
-       "8803      NaN               NaN                  NaN            NaN   \n",
-       "8804      NaN               NaN                  NaN            NaN   \n",
-       "8805      NaN               NaN                  NaN            NaN   \n",
-       "8806      NaN               NaN                  NaN            NaN   \n",
-       "\n",
-       "     Viewership Score  \n",
-       "0                90.0  \n",
-       "1                45.0  \n",
-       "2                76.0  \n",
-       "3                30.0  \n",
-       "4                55.0  \n",
-       "...               ...  \n",
-       "8802              NaN  \n",
-       "8803              NaN  \n",
-       "8804              NaN  \n",
-       "8805              NaN  \n",
-       "8806              NaN  \n",
-       "\n",
-       "[8807 rows x 22 columns]"
-      ]
-     },
-     "execution_count": 54,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "net_titles.join(net_top10)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "966833da",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.7"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..62da6f3
--- /dev/null
+++ b/README.md
@@ -0,0 +1 @@
+# Data-Science
\ No newline at end of file

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