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Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

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README.md

Original

Python for Data Analysis, 3rd Edition

Materials and IPython notebooks for "Python for Data Analysis, 3rd Edition" by Wes McKinney, published by O'Reilly Media. Book content including updates and errata fixes can be found for free on my website.

Buy the book on Amazon

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Setup Instructions

Option 1: Using uv (Recommended)

uv is a fast Python package installer and resolver. To get started:

  1. Install uv if you haven't already:
curl -LsSf https://astral.sh/uv/install.sh | sh
  1. Start Jupyter Notebook with all dependencies:
uv run jupyter notebook

That's it! uv will automatically create a virtual environment and install all required packages from pyproject.toml.

Option 2: Using Conda

  1. Create a new conda environment:
conda create -n pydata-book python=3.11
conda activate pydata-book
  1. Install dependencies:
pip install -r requirements.txt
  1. Start Jupyter Notebook:
jupyter notebook

Note: This project uses pandas 2.0.3 to ensure compatibility with the notebooks.

2nd Edition Readers

If you are reading the 2nd Edition (published in 2017), please find the reorganized book materials on the 2nd-edition branch.

1st Edition Readers

If you are reading the 1st Edition (published in 2012), please find the reorganized book materials on the 1st-edition branch.

IPython Notebooks:

License

Code

The code in this repository, including all code samples in the notebooks listed above, is released under the MIT license. Read more at the Open Source Initiative.

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