Reproducible data analysis in Python notebooks.
What it does
Guides the development of reproducible Python data analyses and clearly structured notebooks with informative visualizations.
When to use it
Use when working on data analysis code and Jupyter notebooks.
How to use it
It changes how the agent develops Python data analysis code and Jupyter notebooks, emphasizing reproducibility, vectorized operations, and clear presentation.
What you provide
- An existing project
Latest review
What you need · 6
Lists pandas as a key dependency and directs its use for data manipulation and analysis.
Lists numpy as a key dependency.
Lists matplotlib as a key dependency.
Lists seaborn as a key dependency.
Access · 0
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