wesm/pydata-book
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Materialien und IPython-Notebooks zu „Python for Data Analysis“ von Wes McKinney, veröffentlicht von O'Reilly Media
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README.md
OriginalPython 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.
Setup Instructions
Option 1: Using uv (Recommended)
uv is a fast Python package installer and resolver. To get started:
- Install uv if you haven't already:
curl -LsSf https://astral.sh/uv/install.sh | sh
- 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
- Create a new conda environment:
conda create -n pydata-book python=3.11
conda activate pydata-book
- Install dependencies:
pip install -r requirements.txt
- 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:
- Chapter 2: Python Language Basics, IPython, and Jupyter Notebooks
- Chapter 3: Built-in Data Structures, Functions, and Files
- Chapter 4: NumPy Basics: Arrays and Vectorized Computation
- Chapter 5: Getting Started with pandas
- Chapter 6: Data Loading, Storage, and File Formats
- Chapter 7: Data Cleaning and Preparation
- Chapter 8: Data Wrangling: Join, Combine, and Reshape
- Chapter 9: Plotting and Visualization
- Chapter 10: Data Aggregation and Group Operations
- Chapter 11: Time Series
- Chapter 12: Introduction to Modeling Libraries in Python
- Chapter 13: Data Analysis Examples
- Appendix A: Advanced NumPy
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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