Selecting Pandas Columns by dtype

Question

I was wondering if there is an elegant and shorthand way in Pandas DataFrames to select columns by data type (dtype). i.e. Select only int64 columns from a DataFrame.

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Answer 1

I'd like to extend existing answer by adding options for selecting all floating dtypes or all integer dtypes:

Demo:

np.random.seed(1234)

df = pd.DataFrame({
        'a':np.random.rand(3), 
        'b':np.random.rand(3).astype('float32'), 
        'c':np.random.randint(10,size=(3)).astype('int16'),
        'd':np.arange(3).astype('int32'), 
        'e':np.random.randint(10**7,size=(3)).astype('int64'),
        'f':np.random.choice([True, False], 3),
        'g':pd.date_range('2000-01-01', periods=3)
     })

yields:

In [2]: df
Out[2]:
          a         b  c  d        e      f          g
0  0.191519  0.785359  6  0  7578569  False 2000-01-01
1  0.622109  0.779976  8  1  7981439   True 2000-01-02
2  0.437728  0.272593  0  2  2558462   True 2000-01-03

In [3]: df.dtypes
Out[3]:
a           float64
b           float32
c             int16
d             int32
e             int64
f              bool
g    datetime64[ns]
dtype: object

Selecting all floating number columns:

In [4]: df.select_dtypes(include=['floating'])
Out[4]:
          a         b
0  0.191519  0.785359
1  0.622109  0.779976
2  0.437728  0.272593

In [5]: df.select_dtypes(include=['floating']).dtypes
Out[5]:
a    float64
b    float32
dtype: object

Selecting all integer number columns:

In [6]: df.select_dtypes(include=['integer'])
Out[6]:
   c  d        e
0  6  0  7578569
1  8  1  7981439
2  0  2  2558462

In [7]: df.select_dtypes(include=['integer']).dtypes
Out[7]:
c    int16
d    int32
e    int64
dtype: object

Selecting all numeric columns:

In [8]: df.select_dtypes(include=['number'])
Out[8]:
          a         b  c  d        e
0  0.191519  0.785359  6  0  7578569
1  0.622109  0.779976  8  1  7981439
2  0.437728  0.272593  0  2  2558462

In [9]: df.select_dtypes(include=['number']).dtypes
Out[9]:
a    float64
b    float32
c      int16
d      int32
e      int64
dtype: object