You can use the following methods with the pandas isin() function to filter based on multiple columns in a pandas DataFrame:
Method 1: Filter where Multiple Columns Are Equal to Specific Values
df = df[df[['team', 'position']].isin(['A', 'Guard']).all(axis=1)]
This particular example filters the DataFrame for rows where the team column is equal to ‘A’ and the position column is equal to ‘Guard.’
Method 2: Filter where At Least One Column is Equal to Specific Value
df = df[df[['team', 'position']].isin(['A', 'Guard']).any(axis=1)]
This particular example filters the DataFrame for rows where the team column is equal to ‘A’ or the position column is equal to ‘Guard.’
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({'team': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'], 'position': ['Guard', 'Guard', 'Forward', 'Forward', 'Guard', 'Guard', 'Forward', 'Forward'], 'points': [11, 18, 10, 22, 26, 35, 19, 12]}) #view DataFrame print(df) team position points 0 A Guard 11 1 A Guard 18 2 A Forward 10 3 A Forward 22 4 B Guard 26 5 B Guard 35 6 B Forward 19 7 B Forward 12
Example 1: Filter where Multiple Columns Are Equal to Specific Values
We can use the following syntax to filter the DataFrame to only contain rows where the team column is equal to ‘A’ and the position column is equal to ‘Guard.’
#filter rows where team column is 'A' and position column is 'Guard' df = df[df[['team', 'position']].isin(['A', 'Guard']).all(axis=1)] #view filtered DataFrame print(df) team position points 0 A Guard 11 1 A Guard 18
Notice that only the rows where the team column is equal to ‘A’ and the position column is equal to ‘Guard’ remain in the filtered DataFrame.
Example 2: Filter where At Least One Column is Equal to Specific Value
We can use the following syntax to filter the DataFrame to only contain rows where the team column is equal to ‘A’ or the position column is equal to ‘Guard.’
#filter rows where team column is 'A' or position column is 'Guard' df = df[df[['team', 'position']].isin(['A', 'Guard']).any(axis=1)] #view filtered DataFrame print(df) team position points 0 A Guard 11 1 A Guard 18 2 A Forward 10 3 A Forward 22 4 B Guard 26 5 B Guard 35
Notice that only the rows where the team column is equal to ‘A’ or the position column is equal to ‘Guard’ remain in the filtered DataFrame.
Note: You can find the complete documentation for the pandas isin() function here.
Additional Resources
The following tutorials explain how to perform other common tasks in pandas:
Pandas: How to Add Filter to Pivot Table
Pandas: How to Filter for “Not Contains”
Pandas: How to Filter Rows that Contain a Specific String