Filtering Rows

Most questions keep only some rows: flats under 1000 a month, patients over 60. A comparison on a column gives True or False per row, a mask:

flats = pd.DataFrame({
    "area": ["North", "Center", "East", "Center", "West"],
    "rooms": [2, 1, 3, 3, 2],
    "rent": [950, 1200, 1100, 1650, 800],
})
print(flats[flats["rent"] < 1000])

Inside the table's brackets, the mask keeps the True rows, with their labels:

    area  rooms  rent
0  North      2   950
4   West      2   800

Join conditions with & (both) or | (either), each in its own parentheses, as with array masks:

print(flats[(flats["rooms"] >= 2) & (flats["rent"] < 1200)])

This prints:

    area  rooms  rent
0  North      2   950
2   East      3  1100
4   West      2   800

Text works too: flats["area"] == "Center". And .shape[0] counts the rows that matched.