Python for Data Science — Cheat Sheet Bundle (Pandas, NumPy, Matplotlib)

Description

Stop Googling the same Pandas syntax for the fifth time this week. This cheat sheet bundle puts every essential Python data science command on four compact reference pages you can keep open alongside your Jupyter notebook. The Pandas sheet covers 7 categories of operations with working code examples: data loading (CSV, Excel, JSON, SQL, dict), inspection commands, selection methods (loc, iloc, boolean indexing, query), data cleaning (dropna, fillna, drop, rename, dedup, type casting), aggregation and groupby, merging and concatenation, and window functions including rolling averages and cumulative sums. The NumPy sheet covers array creation (zeros, ones, arange, linspace, random), array manipulation (reshape, flatten, transpose, concatenate, split), mathematical operations (sum, mean, std, dot, matmul, log, exp), and boolean indexing with where and argsort. The Matplotlib & Seaborn sheet covers all plot types with their function signatures, customisation commands (titles, labels, limits, grid, figsize), subplot layouts, and the most-used Seaborn functions (heatmap, pairplot, boxplot, distplot, lineplot). The scikit-learn sheet covers the complete ML pipeline: train/test split with parameters, preprocessing classes, model fitting and prediction, evaluation metrics and cross-validation. All code is Python 3.10+ compatible and tested.