如何使用数据框信息来分隔不同列表中的不同类型的列？

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

如何获取对象类型列存储在l1 = [id，term ..]和float64类型存储在l2 = [member_id，loan_amnt ...] 感谢那些熟悉熊猫帮助的人

Answer 1

您可以使用select_dtypes

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

或使用dtypes

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