Selecting Rows with loc & iloc

Pandas provides two main indexers for selecting rows: loc (label-based) and iloc (position-based).

iloc: Position-Based Selection

Use iloc with integer positions (like list indexing):

loc: Label-Based Selection

Use loc with index labels:

Selecting Rows and Columns Together

Both loc and iloc can select rows AND columns:

Negative Indexing with iloc

Access from the end using negative indices:

Selecting Single Values

Use .at and .iat for scalar access:

Exercise: Row Selection

Exercise: loc Selection

Key Points

• iloc uses integer positions (0, 1, 2, ...)
• loc uses index labels
• Both support [rows, columns] syntax
• Slicing with loc includes the end label
• Slicing with iloc excludes the end position
• Use .at/.iat for fast single-value access