pandas data frame transform INT64 columns to boolean

df['column_name'] = df['column_name'].astype('bool')

For example:

import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.random_integers(0,1,size=5), 
                  columns=['foo'])
print(df)
#    foo
# 0    0
# 1    1
# 2    0
# 3    1
# 4    1

df['foo'] = df['foo'].astype('bool')
print(df)

yields

     foo
0  False
1   True
2  False
3   True
4   True

Given a list of column_names, you could convert multiple columns to bool dtype using:

df[column_names] = df[column_names].astype(bool)

If you don’t have a list of column names, but wish to convert, say, all numeric columns, then you could use

column_names = df.select_dtypes(include=[np.number]).columns
df[column_names] = df[column_names].astype(bool)