You can use the following methods to filter for rows that contain a string with a specific length in a pandas DataFrame:

Method 1: Filter Rows Based on String Length in One Column

#filter rows where col1 has a string length of 5
df.loc[df['col1'].str.len() == 5]

Method 2: Filter Rows Based on String Length of Multiple Columns

#filter rows where col1 has string length of 5 and col2 has string length of 7
df.loc[(df['col1'].str.len() == 5) & (df['col2'].str.len() == 7)]

The following examples show how to use each method in practice with the following pandas DataFrame:

import pandas as pd

#create DataFrame
df = pd.DataFrame({'conf': ['East', 'East', 'North', 'West', 'North', 'South'],
                   'pos': ['Guard', 'Guard', 'Forward', 'Center', 'Center', 'Forward'],
                   'points': [5, 7, 7, 9, 12, 9]})

#view DataFrame
print(df)

    conf      pos  points
0   East    Guard       5
1   East    Guard       7
2  North  Forward       7
3   West   Center       9
4  North   Center      12
5  South  Forward       9

Example 1: Filter Rows Based on String Length in One Column

The following code shows how to filter for rows in the DataFrame that have a string length of 5 in the conf column:

#filter rows where conf has a string length of 5
df.loc[df['conf'].str.len() == 5]

	conf	pos	points
2	North	Forward      7
4	North	Center	    12
5	South	Forward	     9

Only the rows where the conf column has a string length of 5 are returned.

We can see that two different strings met this criteria in the conf column:

• “North”
• “South”

Both strings have a length of 5.

Example 2: Filter Rows Based on String Length of Multiple Columns

The following code shows how to filter for rows in the DataFrame that have a string length of 5 in the conf column and a string length of 7 in the pos column:

#filter rows where conf has string length of 5 and pos has string length of 7
df.loc[(df['conf'].str.len() == 5) & (df['pos'].str.len() == 7)]

        conf	pos	points
2	North	Forward	     7
5	South	Forward	     9

Note: You can find the complete documentation for the str.len() function in pandas .

Additional Resources

The following tutorials explain how to perform other common operations in pandas: