Data Analysis · pandas Core · lesson 7 of 12

Filtering and sorting

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Selecting rows by condition

Filtering a DataFrame uses the same boolean masks as NumPy:

df[df["temp"] > 20]
df[(df["temp"] > 10) & (df["city"] != "Oslo")]

The same rule applies: & and |, never and and or, and brackets around each condition.

Two conveniences worth knowing:

df[df["city"].isin(["London", "Oslo"])]     # membership
df[df["city"].str.startswith("L")]          # string methods live under .str

Sorting returns a new frame:

df.sort_values("temp")                            # ascending
df.sort_values("temp", ascending=False)           # descending
df.sort_values(["band", "temp"])                  # by two columns

Your turn: select the cities above 10 degrees, and produce the city names ordered from warmest to coldest.

You start from this, and edit it in the browser:

import pandas as pd

df = pd.DataFrame({
    "city": ["London", "Lisbon", "Oslo", "Tokyo", "Nairobi"],
    "temp": [14, 24, 3, 19, 26],
})

# Set mild (a DataFrame) and warmest_first (a list of city names).