Selecting & Filtering Data in Pandas

Selecting & Filtering Data

Pandas provides expressive syntax for subsetting.

Selecting rows by label with .loc

df.loc[10:20]   # rows with index 10‑20 inclusive

Selecting rows by integer location with .iloc

df.iloc[:3]    # first three rows

Boolean indexing

df_filtered = df[df['age'] > 30]

Combining multiple conditions

mask = (df['salary'] > 50000) & (df['department'] == 'Engineering')
engineers = df[mask]

Using .query for SQL‑like syntax

df.query('salary > 80000 and age < 40')