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pandas Essentials

by LucidPlexus
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The pandas you use every day, with what each line prints. Two A4 pages on pandas 3: reading a CSV and the options that matter, inspecting a DataFrame, selecting with loc and iloc, filtering with masks, isin, between and query, sorting, new…
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The pandas you use every day, with what each line prints.

Two A4 pages on pandas 3: reading a CSV and the options that matter, inspecting a DataFrame, selecting with loc and iloc, filtering with masks, isin, between and query, sorting, new columns with assign, np.where and np.select, when to use apply, groupby, pivot tables, merge, duplicates, dates and writing out.

Every snippet runs on the LucidPlexus book datasets (Clearstone's budget and invoices, Lanternfield's startups, HealSync's claims and sessions, the agricultural prices), and its real output is printed under it. That includes the traps: a coverage type of "None" that read_csv turns into a missing value, and groupby then dropping those 40 rows (39 claims: one claim is recorded twice).

It notes what changed in pandas 3 and ends with a checklist before you trust a DataFrame.

PDF to print, and an HTML version to read on screen.

#cheat-sheet #data-analysis #data-cleaning #pandas #python
Type Cheat Sheet
Pages 2
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