(pandas)
The table library every data analyst and data scientist reaches for first — learned through fun exercises, in about half an hour.
A free, hands-on course on the basics of pandas — Python's library for working with tables of data. DataFrames, selecting and filtering rows, adding columns, cleaning missing data, and grouping and aggregating, each taught with a fun exercise you solve yourself. Runs entirely on your laptop.
pandas is how data actually gets loaded, cleaned, filtered and summarized in Python — the everyday workhorse behind data analysis, dashboards, and the data prep for every machine-learning model.
Install pandas and meet its two data structures — the Series and the DataFrame — then peek at a table with head, shape, dtypes and info.
Pick out columns, grab rows by label with .loc and by position with .iloc, and filter rows by condition with boolean masks.
Create new columns from arithmetic on existing ones, transform text with .str, and derive labels with .apply — all vectorized, no loops.
Real data has holes. Spot NaN with isna, drop incomplete rows with dropna, or fill the gaps with fillna.
The most powerful move in pandas: split rows into groups, compute a summary for each, and combine the results back into a table.