CODEWITHSUNDEEP
pythonpandasdataframe
Leon
Leon

Reputation: 429

how to use dataframe info to Seperate different types of column in different list?

LoanStats_securev1_2018Q1.info(verbose=True)
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 107866 entries, 0 to 107865
Data columns (total 151 columns):
id                                            object
member_id                                     float64
loan_amnt                                     float64
funded_amnt                                   float64
funded_amnt_inv                               float64
term                                          object
int_rate                                      object
installment                                   float64
grade                                         object
sub_grade                                     object
emp_title                                     object
emp_length                                    object
home_ownership                                object
...
settlement_status                             object
settlement_date                               object
settlement_amount                             float64
settlement_percentage                         float64
settlement_term                               float64
dtypes: float64(119), object(32)
memory usage: 124.3+ MB

how could I get object type colums store in l1=[id,term..] and float64 type in l2=[member_id,loan_amnt...] thanks for someone who familiar with pandas helping

Upvotes: 0

Views: 34

Answers (1)

BENY
BENY

Reputation: 323236

You can using select_dtypes

df.select_dtypes('object').columns.tolist()

Or using dtypes

df.dtypes.reset_index().groupby(0)['index'].apply(list)

Upvotes: 1

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