Run interactive Python notebooks with Jupyter. Covers JupyterLab setup, cell types, keyboard shortcuts, magic commands, nbconvert export, and common pitfalls.
Create and manipulate N-dimensional arrays with NumPy. Covers array creation, broadcasting, vectorized math, indexing, and matrix operations.
Load, filter, transform, and aggregate tabular data with pandas. Covers DataFrame creation, read_csv, groupby, merge, and the SettingWithCopy pitfall.
Pattern-action language for structured text. Field splitting, built-in variables, arithmetic, string functions, arrays, BEGIN/END blocks, and practical data-processing recipes.
Slice, filter, map, and transform JSON data from the command line. Covers all essential filters, built-in functions, select, map, reduce, streaming, and real-world API response processing.
Sort lines (numerically, by field, human-readable sizes), deduplicate with uniq, count lines/words/bytes with wc, and number lines with nl. With real-world pipeline recipes.
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