How to Select Rows in pandas DataFrame Easily

To select a row in pandas, use loc for label-based selection or iloc for position-based selection. You can also select rows by condition using boolean indexing with DataFrame[condition].

Syntax

Here are the main ways to select rows in pandas:

• df.loc[label]: Select row by index label.
• df.iloc[position]: Select row by integer position.
• df[condition]: Select rows where condition is True.

python

df.loc[row_label]
df.iloc[row_position]
df[condition]

Example

This example shows how to select rows by label, position, and condition.

python

import pandas as pd

data = {'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35]}
df = pd.DataFrame(data, index=['a', 'b', 'c'])

# Select row by label 'b'
row_label = df.loc['b']

# Select row by position 2 (third row)
row_position = df.iloc[2]

# Select rows where Age > 28
rows_condition = df[df['Age'] > 28]

print('Row by label b:\n', row_label)
print('\nRow by position 2:\n', row_position)
print('\nRows where Age > 28:\n', rows_condition)

Output

Row by label b:
 Name    Bob
Age      30
Name: b, dtype: object

Row by position 2:
 Name    Charlie
Age          35
Name: c, dtype: object

Rows where Age > 28:
       Name  Age
b      Bob   30
c  Charlie   35

Common Pitfalls

Common mistakes when selecting rows include:

• Using loc with integer positions instead of labels.
• Using iloc with labels instead of positions.
• Forgetting that df[condition] returns multiple rows, not a single row.

Always check if your DataFrame index is default integers or custom labels to choose loc or iloc correctly.

python

import pandas as pd

data = {'Name': ['Alice', 'Bob'], 'Age': [25, 30]}
df = pd.DataFrame(data, index=['x', 'y'])

# Wrong: using iloc with label 'x' (raises error)
# df.iloc['x']  # This will cause an error

# Correct: use loc for label
row = df.loc['x']

print(row)

Output

Name    Alice
Age        25
Name: x, dtype: object

Quick Reference

Method	Description	Example
loc	Select row by index label	df.loc['row_label']
iloc	Select row by integer position	df.iloc[0]
Boolean Indexing	Select rows by condition	df[df['Age'] > 30]

Key Takeaways

Use df.loc[label] to select rows by index label.

Use df.iloc[position] to select rows by integer position.

Use boolean conditions inside df[...] to select rows matching criteria.

Check your DataFrame index type to choose loc or iloc correctly.

Boolean indexing returns all rows matching the condition, not just one.