How to Use filter Method in pandas for Data Selection

The filter method in pandas lets you select rows or columns by specifying labels, like names or patterns. You can use it to keep only columns or rows that match certain criteria, making data selection easy and flexible.

Syntax

The filter method has these main parameters:

• items: List of labels to keep.
• like: String pattern to match labels.
• regex: Regular expression to match labels.
• axis: Choose 0 for rows or 1 for columns (default is columns).

Use one of items, like, or regex to filter labels.

python

DataFrame.filter(items=None, like=None, regex=None, axis=None)

Example

This example shows how to filter columns by name and rows by index labels using filter.

python

import pandas as pd

data = {
    'apple': [1, 2, 3],
    'banana': [4, 5, 6],
    'cherry': [7, 8, 9],
    'date': [10, 11, 12]
}

index_labels = ['a', 'b', 'c']

df = pd.DataFrame(data, index=index_labels)

# Filter columns containing 'a'
filtered_columns = df.filter(like='a', axis=1)

# Filter rows with index labels 'a' and 'c'
filtered_rows = df.filter(items=['a', 'c'], axis=0)

print('Filtered columns (contain "a"):\n', filtered_columns)
print('\nFiltered rows (labels a and c):\n', filtered_rows)

Output

Filtered columns (contain "a"):
    apple  banana
a      1       4
b      2       5
c      3       6

Filtered rows (labels a and c):
    apple  banana  cherry  date
a      1       4       7    10
c      3       6       9    12

Common Pitfalls

Common mistakes when using filter include:

• Not setting axis correctly (default is columns).
• Using multiple filter parameters at once, which can cause unexpected results.
• Trying to filter by values instead of labels (filter works on labels only).

Always check if you want to filter rows (axis=0) or columns (axis=1).

python

import pandas as pd

data = {'A': [1, 2], 'B': [3, 4]}
df = pd.DataFrame(data, index=['x', 'y'])

# Wrong: filtering rows but axis not set (defaults to columns)
wrong_filter = df.filter(items=['x'])  # returns empty DataFrame

# Right: specify axis=0 to filter rows
right_filter = df.filter(items=['x'], axis=0)

print('Wrong filter result:\n', wrong_filter)
print('\nRight filter result:\n', right_filter)

Output

Wrong filter result:
 Empty DataFrame
Columns: [A, B]
Index: []

Right filter result:
    A  B
x  1  3

Quick Reference

Parameter	Description	Default
items	List of labels to keep	None
like	Substring to match labels	None
regex	Regular expression to match labels	None
axis	0 for rows, 1 for columns	1 (columns)

Key Takeaways

Use pandas filter to select rows or columns by label names or patterns.

Set axis=0 to filter rows and axis=1 to filter columns (default).

Use only one of items, like, or regex parameters at a time for clear filtering.

Filter works on labels, not on data values inside the DataFrame.

Check your filter results to avoid empty DataFrames due to wrong axis or labels.