Reproducible Data Analysis in Jupyter
Read OriginalThis article presents a video case study on achieving reproducible data analysis in Jupyter notebooks. It covers loading data, visualization, version control with Git/GitHub, creating Python packages, unit testing with PyTest, and refactoring for speed and debugging, providing a full workflow for robust data science projects.
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