python - 如何使用数据框信息来分隔不同列表中不同类型的列？

Question

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

我怎样才能在 l1=[id,term..] 中获取对象类型的列存储，在 l2=[member_id,loan_amnt...] 中获取 float64 类型，感谢熟悉 pandas 的人的帮助

标签： pythonpandasdataframe

Answer 1

You can using select_dtypes

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

Or using dtypes

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