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What is this?
This is the companion repository of Jupyter notebooks and materials for the book 'Python for Data Analysis' by Wes McKinney, covering pandas, NumPy, and data analysis techniques.
This is the companion repository of Jupyter notebooks and materials for the book 'Python for Data Analysis' by Wes McKinney, covering pandas, NumPy, and data analysis techniques.Is this a standalone library or just notebooks for the book?It's just a set of IPython/Jupyter notebooks that follow the book's chapters, not a library or package you import into other projects.
It's just a set of IPython/Jupyter notebooks that follow the book's chapters, not a library or package you import into other projects.How do I get the notebooks running?Use uv (recommended) to auto-create a virtual environment and install dependencies from pyproject.toml, then launch Jupyter Notebook; alternatively create a conda environment and install the listed dependencies.
Use uv (recommended) to auto-create a virtual environment and install dependencies from pyproject.toml, then launch Jupyter Notebook; alternatively create a conda environment and install the listed dependencies.Do I need a specific pandas version?Yes, the project pins pandas 2.0.3 so the notebooks' output matches the book exactly.
Yes, the project pins pandas 2.0.3 so the notebooks' output matches the book exactly.What if I'm reading an older edition of the book?The repo defaults to the 3rd Edition; readers of the 2nd or 1st Edition need to switch to the dedicated 2nd-edition or 1st-edition git branches, since the main branch material won't match older chapters.
The repo defaults to the 3rd Edition; readers of the 2nd or 1st Edition need to switch to the dedicated 2nd-edition or 1st-edition git branches, since the main branch material won't match older chapters.What topics do the chapters cover?They walk through Python basics, NumPy arrays, pandas fundamentals, data loading/cleaning/wrangling, plotting, aggregation, time series, modeling library intros, and full data analysis examples, plus an advanced NumPy appendix.
They walk through Python basics, NumPy arrays, pandas fundamentals, data loading/cleaning/wrangling, plotting, aggregation, time series, modeling library intros, and full data analysis examples, plus an advanced NumPy appendix.Can I read the book text itself here?No, this repo only has the code notebooks; the full book content with updates and errata is hosted for free on the author's website, or it can be purchased on Amazon.
No, this repo only has the code notebooks; the full book content with updates and errata is hosted for free on the author's website, or it can be purchased on Amazon.What are similar projects?PythonDataScienceHandbook, pandas_exercises, Python-100-Days, mlcourse.ai, Probabilistic-Programming-and-Bayesian-Methods-for-Hackers, Data-Science-For-Beginners, Ai-Learn, 100-Days-Of-ML-Code
PythonDataScienceHandbook, pandas_exercises, Python-100-Days, mlcourse.ai, Probabilistic-Programming-and-Bayesian-Methods-for-Hackers, Data-Science-For-Beginners, Ai-Learn, 100-Days-Of-ML-CodeWhich topics is it in?ipython, notebooks, plotting, loading, analysis, data-processing, time-series, pandas, data-analysis, numpy, jupyter notebook, data-visualization
ipython, notebooks, plotting, loading, analysis, data-processing, time-series, pandas, data-analysis, numpy, jupyter notebook, data-visualization