how to convert boolean column to 0 and 1 by using pd.get

I want to convert all boolean columns in my pandas dataframe into 0 and 1 by using pd.get_dummies. However, the boolean values stay the same after the get_dummies function.

For example:

tmp = pd.DataFrame([  
        ['green' , True],   
        ['red'   , False],   
        ['blue'  , True]]) 
tmp.columns = ['color',  'class'] 
pd.get_dummies(tmp)  
# I have also tried pd.get_dummies(tmp, dtype=int), but got the same output

I got:

   class  color_blue  color_green  color_red
0   True           0            1          0
1  False           0            0          1
2   True           1            0          0

but I need:

   color_blue  color_green  color_red  class_True  class_False
0           0            1          0        1        0
1           0            0          1        0        1
2           1            0          0        1        0

update: My dataframe includes numeric data so convert all columns in the dataframe into string may not be the best soluion.

CodePudding user response：

For processing boolean columns convert them to strings (here are converted all columns):

print (pd.get_dummies(tmp.astype(str)))
   color_blue  color_green  color_red  class_False  class_True
0           0            1          0            0           1
1           0            0          1            1           0
2           1            0          0            0           1

Of convert only boolean:

print (pd.get_dummies(tmp.astype({'class':'str'})))
   color_blue  color_green  color_red  class_False  class_True
0           0            1          0            0           1
1           0            0          1            1           0
2           1            0          0            0           1

You can create dictionary only for boolean columns:

d = dict.fromkeys(tmp.select_dtypes('bool').columns, 'str')
print (pd.get_dummies(tmp.astype(d)))