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Python Data Science Cheatsheet PDF | NumPy, Pandas, Matplotlib Quick Reference

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Highlights

  • Digital download

NumPy, Pandas, Matplotlib, and core stats on one page. Useful when you're mid-analysis and can't remember whether to use df.loc or df.iloc, or whether std() defaults to population or sample variance.

What's included:
- NumPy: array creation, shape and reshape, indexing and slicing, vectorized math operations, boolean masks
- Pandas: DataFrames, read_csv, column selection, row filtering, loc vs iloc, groupby and aggregate, fillna and dropna, sort_values and value_counts
- Matplotlib: line plot, scatter, bar chart, histogram, labels and titles, savefig (call before show() or the figure clears)
- Statistics: mean/median/mode, standard deviation (ddof=0 vs ddof=1 explained), correlation, min-max normalization, z-score standardization
- Common mistakes: chained indexing is unreliable for assignment, plt.show() clears the figure, NumPy and Pandas std() give different answers by default
- Quick tips: df.info(), df.describe(), df.sample() for first-look exploration of any new dataset

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Listed on 07 Aug, 2026
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