You can use the following basic syntax to convert a column of boolean values to a column of integer values in pandas:

df.column1 = df.column1.replace({True: 1, False: 0})

The following example shows how to use this syntax in practice.

Example: Convert Boolean to Integer in Pandas

Suppose we have the following pandas DataFrame:

import pandas as pd

#create DataFrame
df = pd.DataFrame({'team': ['A', 'B', 'C', 'D', 'E', 'F', 'G'],
                   'points': [18, 22, 19, 14, 14, 11, 20],
                   'playoffs': [True, False, False, False, True, False, True]})

#view DataFrame
df

We can use to quickly check the data type of each column:

#check data type of each column
df.dtypes

team        object
points       int64
playoffs      bool
dtype: object

We can see that the ‘playoffs’ column is of type boolean.

We can use the following code to quickly convert the True/False values in the ‘playoffs’ column into 1/0 integer values:

#convert 'playoffs' column to integer
df.playoffs = df.playoffs.replace({True: 1, False: 0})

#view updated DataFrame
df

	team	points	playoffs
0	A	18	1
1	B	22	0
2	C	19	0
3	D	14	0
4	E	14	1
5	F	11	0
6	G	20	1

Each True value was converted to 1 and each False value was converted to 0.

We can use dtypes again to verify that the ‘playoffs’ column is now an integer:

#check data type of each columndf.dtypes

team        object
points       int64
playoffs     int64
dtype: object

We can see that the ‘playoffs’ column is now of type int64.

Additional Resources

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