Pandas: tabular data

If NumPy is arrays, pandas is tables. The DataFrame is the central type — rows, named columns, mixed dtypes.

Essentials

• df["col"] — a Series (one column)
• df[df["x"] > 5] — boolean filter
• df.groupby("col").agg(...) — split-apply-combine
• df.sort_values("col") · df.merge(other, on="key")
• pd.read_csv(io.StringIO(...)) — parse CSVs

Pyodide reality

Pandas is large (~15 MB total with NumPy). First import is slow, then cached. Good for medium data (~100k rows); huge datasets are out of scope for a browser.

Try it

1. Add a country column to df and group by it.
2. Sort by year descending and take the top 3.