pandas - Python : T test ind looping over columns of df

Question

My dataframe is composed of accounting variables and a dummy variable that allows me to identify two types of company. I would like to perform a t-test for every column of my dataframe in order to compare the means of the variables between the two types of company.

For the moment I have separated my df into two different df based on the dummy variable and run the following code:

for column_type1, column_type2 in zip(df_type1.columns[1:],df_type2.columns[1:]):
    print(ttest_ind(column_type1,column_type2, equal_var=False, nan_policy='omit'))

However, I'm getting the following error:

TypeError: cannot perform reduce with flexible type

If you know how to solve this or have a better way to do it your help is more than welcome!

Thanks

**** EDIT & SOLUTION ****

I've come along my issue and here the code for it.

for column_type1, column_type2 in zip(df_type1,df_type2):
    print(ttest_ind(df_type1[column_type1],df_type2[column_type2], equal_var=False, nan_policy='omit'))

Answer 1

for column_type1, column_type2 in zip(df_type1,df_type2):
print(ttest_ind(df_type1[column_type1],df_type2[column_type2], equal_var=False, nan_policy='omit'))