Plotnine/1-Intro.ipynb

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  {
   "cell_type": "code",
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   "source": [
    "'''\r\n",
    "# Using pip\r\n",
    "$ pip install plotnine         # 1. should be sufficient for most\r\n",
    "$ pip install 'plotnine[all]'  # 2. includes extra/optional packages\r\n",
    "'''"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "source": [
    "from plotnine import *\r\n",
    "from plotnine.data import mtcars"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stderr",
     "text": [
      "C:\\Users\\Roja Achary\\Anaconda3\\envs\\lab\\lib\\importlib\\_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject\n",
      "C:\\Users\\Roja Achary\\Anaconda3\\envs\\lab\\lib\\importlib\\_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject\n",
      "C:\\Users\\Roja Achary\\Anaconda3\\envs\\lab\\lib\\importlib\\_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject\n",
      "C:\\Users\\Roja Achary\\Anaconda3\\envs\\lab\\lib\\importlib\\_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "source": [
    "#Scatter plot"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "source": [
    "(ggplot(mtcars, aes('wt', 'mpg'))\r\n",
    " + geom_point())"
   ],
   "outputs": [
    {
     "output_type": "display_data",
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     },
     "metadata": {}
    },
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "<ggplot: (121733928091)>"
      ]
     },
     "metadata": {},
     "execution_count": 9
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "source": [
    "#Scatter plot colored according some variable"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "source": [
    "(ggplot(mtcars, aes('wt', 'mpg', color='factor(gear)'))\r\n",
    " + geom_point())"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/svg+xml": "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\r\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\r\n  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\r\n<!-- Created with matplotlib (https://matplotlib.org/) -->\r\n<svg height=\"312.510977pt\" version=\"1.1\" viewBox=\"0 0 500.138625 312.510977\" width=\"500.138625pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\r\n <metadata>\r\n  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\r\n   <cc:Work>\r\n    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\r\n    <dc:date>2021-08-23T21:32:32.213292</dc:date>\r\n    <dc:format>image/svg+xml</dc:format>\r\n    <dc:creator>\r\n     <cc:Agent>\r\n      <dc:title>Matplotlib v3.3.4, https://matplotlib.org/</dc:title>\r\n     </cc:Agent>\r\n    </dc:creator>\r\n   </cc:Work>\r\n  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     },
     "metadata": {}
    },
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "<ggplot: (121734721470)>"
      ]
     },
     "metadata": {},
     "execution_count": 11
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "source": [
    "#Scatter plot colored according some variable and smoothed with a linear model with confidence intervals."
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "source": [
    "(ggplot(mtcars, aes('wt', 'mpg', color='factor(gear)'))\r\n",
    " + geom_point()\r\n",
    " + stat_smooth(method='lm'))"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/svg+xml": "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\r\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\r\n  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\r\n<!-- Created with matplotlib (https://matplotlib.org/) -->\r\n<svg height=\"309.024687pt\" version=\"1.1\" viewBox=\"0 0 500.138625 309.024687\" width=\"500.138625pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\r\n <metadata>\r\n  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\r\n   <cc:Work>\r\n    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\r\n    <dc:date>2021-08-23T21:32:51.920825</dc:date>\r\n    <dc:format>image/svg+xml</dc:format>\r\n    <dc:creator>\r\n     <cc:Agent>\r\n      <dc:title>Matplotlib v3.3.4, https://matplotlib.org/</dc:title>\r\n     </cc:Agent>\r\n    </dc:creator>\r\n   </cc:Work>\r\n  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.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     },
     "metadata": {}
    },
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "<ggplot: (-9223371915120600653)>"
      ]
     },
     "metadata": {},
     "execution_count": 13
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "source": [
    "#Scatter plot colored according some variable, \r\n",
    "#smoothed with a linear model with confidence intervals and plotted on separate panels."
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "source": [
    "(ggplot(mtcars, aes('wt', 'mpg', color='factor(gear)'))\r\n",
    " + geom_point()\r\n",
    " + stat_smooth(method='lm')\r\n",
    " + facet_wrap('~gear'))"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ],
      "image/svg+xml": "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\r\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\r\n  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\r\n<!-- Created with matplotlib (https://matplotlib.org/) -->\r\n<svg height=\"323.324688pt\" version=\"1.1\" viewBox=\"0 0 500.138625 323.324688\" width=\"500.138625pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\r\n <metadata>\r\n  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\r\n   <cc:Work>\r\n    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\r\n    <dc:date>2021-08-23T21:33:16.172223</dc:date>\r\n    <dc:format>image/svg+xml</dc:format>\r\n    <dc:creator>\r\n     <cc:Agent>\r\n      <dc:title>Matplotlib v3.3.4, https://matplotlib.org/</dc:title>\r\n     </cc:Agent>\r\n    </dc:creator>\r\n   </cc:Work>\r\n  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.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     },
     "metadata": {}
    },
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "<ggplot: (121602975706)>"
      ]
     },
     "metadata": {},
     "execution_count": 15
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "source": [
    "#Make it playful"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "source": [
    "(ggplot(mtcars, aes('wt', 'mpg', color='factor(gear)'))\r\n",
    " + geom_point()\r\n",
    " + stat_smooth(method='lm')\r\n",
    " + facet_wrap('~gear')\r\n",
    " + theme_xkcd())"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ],
      "image/svg+xml": "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\r\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\r\n  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\r\n<!-- Created with matplotlib (https://matplotlib.org/) -->\r\n<svg height=\"318.6105pt\" version=\"1.1\" viewBox=\"0 0 505.04675 318.6105\" width=\"505.04675pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\r\n <metadata>\r\n  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\r\n   <cc:Work>\r\n    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\r\n    <dc:date>2021-08-23T21:33:32.252356</dc:date>\r\n    <dc:format>image/svg+xml</dc:format>\r\n    <dc:creator>\r\n     <cc:Agent>\r\n      <dc:title>Matplotlib v3.3.4, https://matplotlib.org/</dc:title>\r\n     </cc:Agent>\r\n    </dc:creator>\r\n   </cc:Work>\r\n  </rdf:RDF>\r\n 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.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.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.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.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.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"
     },
     "metadata": {}
    },
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "<ggplot: (-9223371915251603105)>"
      ]
     },
     "metadata": {},
     "execution_count": 17
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [],
   "outputs": [],
   "metadata": {}
  }
 ],
 "metadata": {
  "orig_nbformat": 4,
  "language_info": {
   "name": "python",
   "version": "3.6.10",
   "mimetype": "text/x-python",
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "pygments_lexer": "ipython3",
   "nbconvert_exporter": "python",
   "file_extension": ".py"
  },
  "kernelspec": {
   "name": "python3",
   "display_name": "Python 3.6.10 64-bit ('lab': conda)"
  },
  "interpreter": {
   "hash": "ef0af0e2864dd9943b080eef7e89ea34b1917f29e151dc31df9abd8d184eafae"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}