按列NAME选择列dtype

Question

import pandas as pd 
import numpy as np 
cols = ['string',pd.Timestamp('2017-10-13'), 'anotherstring', pd.Timestamp('2017-10-14')] 
pd.DataFrame(np.random.rand(5,4), columns=cols) 

如何才能找回第二和第四列（其中有dtype'date time.datetime'）？列内容的类型完全相同，所以select_dtypes不起作用。

Answer 1

使用type与map：

df = df.loc[:, df.columns.map(type) == pd.Timestamp] 
print (df) 
    2017-10-13 00:00:00 2017-10-14 00:00:00 
0    0.894932    0.502015 
1    0.080334    0.155712 
2    0.600152    0.206344 
3    0.008913    0.919534 
4    0.280229    0.951434 

详情：

print (df.columns.map(type)) 
Index([       <class 'str'>, 
     <class 'pandas._libs.tslib.Timestamp'>, 
           <class 'str'>, 
     <class 'pandas._libs.tslib.Timestamp'>] 

print (df.columns.map(type) == pd.Timestamp) 
[False True False True] 

替代解决方案：

df1 = df.loc[:, [isinstance(i, pd.Timestamp) for i in df.columns]] 
print (df1) 
    2017-10-13 00:00:00 2017-10-14 00:00:00 
0    0.818283    0.128299 
1    0.570288    0.458400 
2    0.857426    0.395963 
3    0.595765    0.306861 
4    0.196899    0.438231