DataFrame selection and cleaning without guessing

Pandas makes selection feel easy: pick columns, filter rows, rename fields, drop bad values. The danger is that easy selection can hide a silent assumption.

In ML data prep, select by column name, not by position. Clean values with rules you can explain. Keep the row count visible after each filter so you know whether your model-ready table still represents the data you meant to train on.