Select feature select_dtypes (include = [] / exclude = []) according to the data type

Select feature select_dtypes (include = [ ''] / exclude = []) according to the data type

In [21]:

df.select_dtypes(include=['object']).columns.values

 

Out[21]:

array(['term', 'loan_status', 'int_rate', 'emp_length', 'home_ownership',
       'verification_status', 'desc', 'purpose', 'title', 'zip_code',
       'addr_state', 'issue_d', 'earliest_cr_line'], dtype=object)

In [22]:

 

df.select_dtypes(exclude=['object']).columns.values

 

Out[22]:

array(['member_id', 'loan_amnt', 'annual_inc', 'dti', 'delinq_2yrs',
       'inq_last_6mths', 'mths_since_last_delinq',
       'mths_since_last_record', 'open_acc', 'pub_rec', 'total_acc',
       'pub_rec_bankruptcies'], dtype=object)