This repository contains examples of how to use three popular libraries for data science in Python: NumPy, Pandas, and Matplotlib.
NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. In this repository, you'll find examples of how to use NumPy to perform basic mathematical operations, manipulate arrays, and more.
Pandas is an open-source data manipulation and analysis library for the Python programming language. In this repository, you'll find examples of how to use Pandas to read in and manipulate data, create data frames, perform statistical analysis, and more.
Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy. In this repository, you'll find examples of how to use Matplotlib to create line graphs, scatter plots, histograms, and more.
To get started with this repository, you'll need to have Python installed on your computer, as well as the three libraries listed above. You can install these libraries using pip, a package manager for Python:
pip install numpy pandas matplotlib
Once you've installed these libraries, you can run the code in the examples directory to see how they work.
If you'd like to contribute to this repository, feel free to fork the project and submit a pull request. We welcome any and all contributions!