Publishing archive
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The highlighted days are the ones with something published; those are clickable.
IT
Not a lesson but a reference page, standing in front of the heavy part of the pandas module. Eight words — a table, a column, a label and a position, a mask, a missing value, a key, a type and a shape — on one table of three rows. Read it once now and come back when a word turns up in a lesson.
IT
The thirtieth lesson of the Python course. Data arrives broken: numbers as text, a city spelled three ways, a duplicate row and an empty cell. `isna`, `to_numeric` with `errors="coerce"`, `astype`, `drop_duplicates` — and the question the lesson turns on: drop a gap or fill it, and what filling it costs.
IT
The twenty-ninth lesson of the Python course. `merge` joins two tables on a key — and by default throws away, in silence, every row that found no match. `inner` and `left`, `indicator`, keys with different names, `join` by label, and the duplicated key that multiplies rows and the sums along with them.
IT
The twenty-eighth lesson of the Python course. `groupby` is a loop written as a question: cut the table by a key, count each piece, put the pieces back. `agg` with column names of your own, two keys, a key the table does not hold, `transform` for a share, the difference between `count` and `size`, and the groups that go missing without a word.
IT
The twenty-seventh lesson of the Python course. A mask is a column of yes and no, and a whole table is filtered with one. `df[mask]`, `.loc[mask, columns]`, `&`, `|`, `~` and the brackets that are not decoration, `isin`, `between`, `str` — and the labels a filter leaves exactly as they were, which is where `loc` and `iloc` finally part company.
