How to Filter a Pandas DataFrame on Multiple Conditions


Often you may want to filter a pandas DataFrame on more than one condition. Fortunately this is easy to do using boolean operations.

This tutorial provides several examples of how to filter the following pandas DataFrame on multiple conditions:

import pandas as pd

#create DataFrame
df = pd.DataFrame({'team': ['A', 'A', 'B', 'B', 'C'],
                   'points': [25, 12, 15, 14, 19],
                   'assists': [5, 7, 7, 9, 12],
                   'rebounds': [11, 8, 10, 6, 6]})

#view DataFrame 
df

        team	points	assists	rebounds
0	A	25	5	11
1	A	12	7	8
2	B	15	7	10
3	B	14	9	6
4	C	19	12	6

Example 1: Filter on Multiple Conditions Using ‘And’

The following code illustrates how to filter the DataFrame using the and (&) operator:

#return only rows where points is greater than 13 and assists is greater than 7
df[(df.points > 13) & (df.assists > 7)]

        team	points	assists	rebounds
3	B	14	9	6
4	C	19	12	6

#return only rows where team is 'A' and points is greater than or equal to 15
df[(df.team == 'A') & (df.points >= 15)]


        team	points	assists	rebounds
0	A	25	5	11

Example 2: Filter on Multiple Conditions Using ‘Or’

The following code illustrates how to filter the DataFrame using the or (|) operator:

#return only rows where points is greater than 13 or assists is greater than 7
df[(df.points > 13) | (df.assists > 7)]


        team	points	assists	rebounds
0	A	25	5	11
2	B	15	7	10
3	B	14	9	6
4	C	19	12	6

#return only rows where team is 'A' or points is greater than or equal to 15
df[(df.team == 'A') | (df.points >= 15)]

        team	points	assists	rebounds
0	A	25	5	11
1	A	12	7	8
2	B	15	7	10
4	C	19	12	6

Example 3: Filter on Multiple Conditions Using a List

The following code illustrates how to filter the DataFrame where the row values are in some list.

#define a list of values
filter_list = [12, 14, 15]

#return only rows where points is in the list of values
df[df.points.isin(filter_list)]

	team	points	assists	rebounds
1	A	12	7	8
2	B	15	7	10
3	B	14	9	6

#define another list of values
filter_list2 = ['A', 'C']

#return only rows where team is in the list of values
df[df.team.isin(filter_list2)]


        team	points	assists	rebounds
0	A	25	5	11
1	A	12	7	8
4	C	19	12	6

You can find more pandas tutorials here.

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