In [1]:

    

import pandas as pd


    

In [2]:

    

df = pd.DataFrame({'a': [1, 2, 1, 3],
                   'b': [0.4, 1.1, 0.1, 0.8],
                   'c': ['X', 'Y', 'X', 'Z'],
                   'd': [[0, 0], [0, 1], [1, 0], [1, 1]],
                   'e': [True, True, False, True]})


    

In [3]:

    

df['f'] = pd.to_datetime(['2018-01-01', '2018-03-15', '2018-02-20', '2018-03-15'])


    

In [4]:

    

print(df)


    

    




   a    b  c       d      e          f
0  1  0.4  X  [0, 0]   True 2018-01-01
1  2  1.1  Y  [0, 1]   True 2018-03-15
2  1  0.1  X  [1, 0]  False 2018-02-20
3  3  0.8  Z  [1, 1]   True 2018-03-15

In [5]:

    

print(df.dtypes)


    

    




a             int64
b           float64
c            object
d            object
e              bool
f    datetime64[ns]
dtype: object

In [6]:

    

print(df.select_dtypes(include=int))


    

    




   a
0  1
1  2
2  1
3  3

In [7]:

    

print(df.select_dtypes(include='int'))


    

    




   a
0  1
1  2
2  1
3  3

In [8]:

    

print(df.select_dtypes(include='int64'))


    

    




   a
0  1
1  2
2  1
3  3

In [9]:

    

print(df.select_dtypes(include='int32'))


    

    




Empty DataFrame
Columns: []
Index: [0, 1, 2, 3]

In [10]:

    

print(df.select_dtypes(include=[int, float, 'datetime']))


    

    




   a    b          f
0  1  0.4 2018-01-01
1  2  1.1 2018-03-15
2  1  0.1 2018-02-20
3  3  0.8 2018-03-15

In [11]:

    

print(df.select_dtypes(include='number'))


    

    




   a    b
0  1  0.4
1  2  1.1
2  1  0.1
3  3  0.8

In [12]:

    

print(df.select_dtypes(include=object))


    

    




   c       d
0  X  [0, 0]
1  Y  [0, 1]
2  X  [1, 0]
3  Z  [1, 1]

In [13]:

    

print(type(df.at[0, 'c']))


    

    




<class 'str'>

In [14]:

    

print(type(df.at[0, 'd']))


    

    




<class 'list'>

In [15]:

    

print(df.select_dtypes(exclude='number'))


    

    




   c       d      e          f
0  X  [0, 0]   True 2018-01-01
1  Y  [0, 1]   True 2018-03-15
2  X  [1, 0]  False 2018-02-20
3  Z  [1, 1]   True 2018-03-15

In [16]:

    

print(df.select_dtypes(exclude=[bool, 'datetime']))


    

    




   a    b  c       d
0  1  0.4  X  [0, 0]
1  2  1.1  Y  [0, 1]
2  1  0.1  X  [1, 0]
3  3  0.8  Z  [1, 1]

In [17]:

    

print(df.select_dtypes(include='number', exclude=int))


    

    




     b
0  0.4
1  1.1
2  0.1
3  0.8

In [18]:

    

# print(df.select_dtypes(include=[int, bool], exclude=int))
# ValueError: include and exclude overlap on frozenset({<class 'numpy.int64'>})