Pandas Series filter()

import pandas as pd

# create a Series
data = pd.Series([1, 2, 3, 4, 5], index=['a', 'b', 'c', 'd', 'e'])

# use filter() to select elements
filtered_data = data.filter(items=['b', 'd'])

print(filtered_data)

'''
Output 

b    2
d    4
dtype: int64

'''

filter() Syntax

The syntax of the filter() method in Pandas is:

Series.filter(items=None, like=None, regex=None)

filter() Arguments

The filter() method takes following arguments:

• items (optional) - a list containing the labels of the indices you want to keep in the Series
• like (optional) - a string that represents a substring to match in the index labels
• regex (optional) - a regular expression pattern

filter() Return Value

The filter() method returns the selected elements based on specified conditions, such as index names, substrings within the index labels, or regular expression patterns.

Example 1: Use items Parameter to Select Specific Indices

import pandas as pd

# create a Series
data = pd.Series([10, 20, 30, 40, 50], index=['apple', 'banana', 'carrot', 'date', 'elderberry'])

# use items parameter to select specific indices
filtered_by_items = data.filter(items=['banana', 'date'])

print("Filtered by items:\n", filtered_by_items)

Output

Filtered by items:
banana    20
date      40
dtype: int64

In the above example, we first created the data Series with values [10, 20, 30, 40, 50] and corresponding indices ['apple', 'banana', 'carrot', 'date', 'elderberry'].

Then, we used the filter() method with the items parameter to select elements from the data Series that have the indices banana and date.

Example 2: Use like Parameter to Select Indices That Contain a Substring

import pandas as pd

# create a Series
data = pd.Series([10, 20, 30, 40, 50], index=['apple', 'banana', 'carrot', 'date', 'elderberry'])

# use like parameter to select indices that contain a substring
filtered_by_like = data.filter(like='e')

print("\nFiltered by like:\n", filtered_by_like)

Output

Filtered by like:
apple         10
date           40
elderberry  50
dtype: int64

In this example, we used the filter() method with the like parameter to select indices in the Series that contain the letter e.

Example 3: Select Indices Using Regular Expression Pattern

import pandas as pd

# create a Series
data = pd.Series([10, 20, 30, 40, 50], index=['apple', 'banana', 'carrot', 'date', 'elderberry'])

# use regex parameter to select indices based on a regular expression pattern
filtered_by_regex = data.filter(regex=r'^[a-d]')

print("Filtered by regex:\n", filtered_by_regex)

Output

Filtered by regex:
apple     10
banana    20
carrot    30
date      40
dtype: int64

Here, we used the filter() function with the regex parameter set to r'^[a-d]'.

As a result, filtered_by_regex will contain only elements with index labels starting from a to d.

Note: To learn more about Regular Expressions, please visit Python RegEx.