You can use the following basic syntax to convert a Boolean column to a string column in a pandas DataFrame:

df['my_bool_column'] = df['my_bool_column'].replace({True: 'True', False: 'False'})

This particular example replaces each True value with the string ‘True’ and each False value with the string ‘False’ in the column called my_bool_column.

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

Example: Convert Boolean to String 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': [18,20, 25, 40, 34, 32, 19],
                   'all_star': [True, False, True, True, True, False, False],
                   'starter': [False, True, True, True, False, False, False]})

#view DataFrame
print(df)

  team  points  all_star  starter
0    A      18      True    False
1    B      20     False     True
2    C      25      True     True
3    D      40      True     True
4    E      34      True    False
5    F      32     False    False
6    G      19     False    False

We can use the dtypes function to check the data type of each column in the DataFrame:

#view data type of each column
print(df.dtypes)

team        object
points       int64
all_star      bool
starter       bool
dtype: object

From the output we can see that the all_star and starter columns are both Booleans.

We can use the following syntax to convert the all_star column to a string column:

#convert Boolean values in all_star column to strings
df['all_star'] = df['all_star'].replace({True: 'True', False: 'False'})

#view updated DataFrame
print(df)

  team  points all_star  starter
0    A      18     True    False
1    B      20    False     True
2    C      25     True     True
3    D      40     True     True
4    E      34     True    False
5    F      32    False    False
6    G      19    False    False

#view updated data types of each column
print(df.dtypes)

team        object
points       int64
all_star    object
starter       bool
dtype: object

From the output we can see that the all_star column has been converted to a string column.

To convert the all_star and starter columns both from Boolean to strings, we can use the following syntax:

#convert Boolean values in all_star and starter columns to strings
df[['all_star', 'starter']] = df[['all_star', 'starter']].replace({True: 'True', False: 'False'})

#view updated DataFrame
print(df)

  team  points all_star  starter
0    A      18     True    False
1    B      20    False     True
2    C      25     True     True
3    D      40     True     True
4    E      34     True    False
5    F      32    False    False
6    G      19    False    False

#view updated data types of each column
print(df.dtypes)

team        object
points       int64
all_star    object
starter     object
dtype: object

From the output we can see that both Boolean columns have been converted to strings.

Note: You can find the complete documentation for the pandas replace() function .

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