Pandas: How to Filter Rows that Contain a Specific String


You can use the following syntax to filter for rows that contain a certain string in a pandas DataFrame:

df[df["col"].str.contains("this string")]

This tutorial explains several examples of how to use this syntax in practice with the following DataFrame:

import pandas as pd

#create DataFrame
df = pd.DataFrame({'team': ['A', 'A', 'A', 'B', 'B', 'C'],
                   'conference': ['East', 'East', 'East', 'West', 'West', 'East'],
                   'points': [11, 8, 10, 6, 6, 5]})

#view DataFrame
df

        team	conference   points
0	A	East         11
1	A	East	     8
2	A	East	     10
3	B	West         6
4	B	West         6
5	C	East         5

Example 1: Filter Rows that Contain a Specific String

The following code shows how to filter for rows in the DataFrame that contain ‘A’ in the team column:

df[df["team"].str.contains("A")]

	team	conference points
0	A	East	   11
1	A	East	   8
2	A	East	   10

Only the rows where the team column contains ‘A’ are kept.

Example 2: Filter Rows that Contain a String in a List

The following code shows how to filter for rows in the DataFrame that contain ‘A’ or ‘B’ in the team column:

df[df["team"].str.contains("A|B")]

	team	conference points
0	A	East	   11
1	A	East	   8
2	A	East	   10
3	B	West	   6
4	B	West	   6

Only the rows where the team column contains ‘A’ or ‘B’ are kept.

Example 3: Filter Rows that Contain a Partial String

In the previous examples, we filtered based on rows that exactly matched one or more strings.

However, if we’d like to filter for rows that contain a partial string then we can use the following syntax:

#identify partial string to look for
keep= ["Wes"]

#filter for rows that contain the partial string "Wes" in the conference column
df[df.conference.str.contains('|'.join(keep))]

	team	conference points
3	B	West	   6
4	B	West	   6

Only the rows where the conference column contains “Wes” are kept.

Additional Resources

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

How to Drop Rows in Pandas DataFrame Based on Condition
How to Filter a Pandas DataFrame on Multiple Conditions
How to Use “NOT IN” Filter in Pandas DataFrame

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