pandas data frame transform INT64 columns to boolean

Question

Some column in dataframe df, df.column, is stored as datatype int64.

The values are all 1s or 0s.

Is there a way to replace these values with boolean values?

Answer 1

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)