python - 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.

To elaborate, something along the lines of

df.select_columns(dtype=float64)

Thanks in advance for the help

Answer 1

Since 0.14.1 there's a select_dtypes method so you can do this more elegantly/generally.

In [11]: df = pd.DataFrame([[1, 2.2, 'three']], columns=['A', 'B', 'C'])

In [12]: df.select_dtypes(include=['int'])
Out[12]:
   A
0  1

To select all numeric types use the numpy dtype numpy.number

In [13]: df.select_dtypes(include=[np.number])
Out[13]:
   A    B
0  1  2.2

In [14]: df.select_dtypes(exclude=[object])
Out[14]:
   A    B
0  1  2.2