I have a pandas dataframe with boolean values, i.e.
col1 col2
1 True False
2 False True
3 True True
when I use pandas' DataFrame.to_csv method, the resulting dataframe looks like
,col1,col2
1,True,False
2,False,True
3,True,True
is there a way to write the boolean variables as 1s and 0s (more space-efficient), i.e.
,col1,col2
1,1,0
2,0,1
3,1,1
without having to cast the entire dataframe first?
It's quite simple actually, just multiply the df by 1.
import pandas as pd
import io
data = """
col1 col2
1 True False
2 False True
3 True True
"""
df = pd.read_csv(io.StringIO(data), delimiter='\s+')
print(df*1)
This will change it to:
col1 col2
1 1 0
2 0 1
3 1 1
From there you can either reassign the df from within the code by doing df = df*1 or df2 = df*1. The first will prevent duplicate copy.
You can just convert the dtype of the df to int this will convert True to 1 and False to 0:
In [16]:
df.astype(int)
Out[16]:
col1 col2
1 1 0
2 0 1
3 1 1
