You can use the following syntax to drop rows that contain a certain string in a pandas DataFrame:
df[df["col"].str.contains("this string")==False]
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: Drop Rows that Contain a Specific String
The following code shows how to drop all rows in the DataFrame that contain ‘A’ in the team column:
df[df["team"].str.contains("A")==False] team conference points 3 B West 6 4 B West 6 5 C East 5
Example 2: Drop Rows that Contain a String in a List
The following code shows how to drop all rows in the DataFrame that contain ‘A’ or ‘B’ in the team column:
df[df["team"].str.contains("A|B")==False] team conference points 5 C East 5
Example 3: Drop Rows that Contain a Partial String
In the previous examples, we dropped rows based on rows that exactly matched one or more strings.
However, if we’d like to drop rows that contain a partial string then we can use the following syntax:
#identify partial string to look for discard = ["Wes"] #drop rows that contain the partial string "Wes" in the conference column df[~df.conference.str.contains('|'.join(discard))] team conference points 0 A East 11 1 A East 8 2 A East 10 5 C East 5
You can find more pandas tutorials on this page.