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02 — Data Analysis

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Tabular data manipulation and scientific computing: pandas, NumPy, Polars, SciPy, and statsmodels.

Scope

Cheat sheets for array computing, tabular data wrangling, scientific statistics, and statistical modeling. Visualization belongs to 03-Data-Visualization; predictive ML to 04-Machine-Learning.

Cheat Sheets

Cheat Sheet Description
numpy.md Arrays, dtypes, broadcasting, vectorized math, random, linear algebra, performance
pandas.md Series & DataFrames: I/O, cleaning, groupby, merge/join/concat, pivot/reshape, datetime, strings, categoricals
polars.md Fast Rust-based DataFrames: expression API, lazy evaluation, large-file workflows
scipy.md stats & hypothesis tests, optimization, sparse matrices, interpolation, signal/image processing
statsmodels.md OLS/GLM/logit regression, formula API, diagnostics, ANOVA, time-series (ARIMA, ETS)

Planned Cheat Sheets

  • Time Series Analysis with pandas — resampling, rolling windows, feature engineering for forecasts

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