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.

<

Answer 1

Multiple includes for selecting columns with list of types for example- float64 and int64

df_numeric = df.select_dtypes(include=[np.float64,np.int64])

Answer 2

You can use :

for i in x.columns[x.dtypes == 'object']:   print(i)

incase you just want to display only the column names of a particular dataframe rather than a sliced dataframe. Don't know if any function as such exits for python.

PS : replace object with the datatype you want.

Answer 3

select_dtypes(include=[np.int])