📊 Python Libraries for Data Analysis & Visualization
This repository contains essential Python libraries for data analysis and visualization, including NumPy, Pandas, Matplotlib, and Seaborn. These libraries help with numerical computations, data manipulation, and creating insightful visualizations.
📌 Table of Contents
📥 Installation
📚 Libraries Overview
📊 Usage Examples
NumPy
Pandas
Matplotlib
Seaborn
📥 Installation
To install these libraries, run the following command:
pip install numpy pandas matplotlib seaborn
📚 Libraries Overview
🔹 NumPy - High-performance multidimensional array computations.
🔹 Pandas - Data manipulation and analysis using DataFrames.
🔹 Matplotlib - Customizable visualizations and plots.
🔹 Seaborn - Advanced statistical data visualization built on Matplotlib.
📊 Usage Examples
NumPy - Numerical Computing
import numpy as np
arr = np.array([1, 2, 3, 4, 5])
print("NumPy Array:", arr)
Pandas - Data Manipulation
import pandas as pd
data = {'Name': ['Alice', 'Bob'], 'Age': [25, 30]}
df = pd.DataFrame(data)
print(df)
Matplotlib - Data Visualization
import matplotlib.pyplot as plt
x = [1, 2, 3, 4, 5]
y = [10, 20, 25, 30, 50]
plt.plot(x, y, marker='o', linestyle='--', color='r')
plt.title("Sample Line Plot")
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
plt.show()
Seaborn - Statistical Visualization
import seaborn as sns
import matplotlib.pyplot as plt
tips = sns.load_dataset('tips')
sns.scatterplot(x='total_bill', y='tip', data=tips, hue='sex', style='time')
plt.title("Seaborn Scatter Plot")
plt.show()
🤝 Contributing
🔥 Want to contribute? Follow these steps:
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Fork the repository.
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Clone it to your local machine.
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Create a new branch:
git checkout -b feature-branch
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Make improvements and commit changes.
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Push the branch and create a Pull Request (PR).
📢 We welcome all suggestions and contributions!
📜 License
This project is licensed under the MIT License – you are free to use and modify it.
🚀 Let's Learn and Build Together!
💡 This repository is designed to help you master data analysis and visualization. Keep exploring, experimenting, and sharing knowledge!
🔗 Follow for more updates & projects!
🔥 Happy Coding! 😊