How do I find numeric columns in Pandas?

You could use select_dtypes method of DataFrame. It includes two parameters include and exclude. So isNumeric would look like:

numerics = ['int16', 'int32', 'int64', 'float16', 'float32', 'float64']newdf = df.select_dtypes(include=numerics)

Simple one-line answer to create a new dataframe with only numeric columns:

df.select_dtypes(include=np.number)

If you want the names of numeric columns:

df.select_dtypes(include=np.number).columns.tolist()

Complete code:

import pandas as pdimport numpy as npdf = pd.DataFrame({'A': range(7, 10),                   'B': np.random.rand(3),                   'C': ['foo','bar','baz'],                   'D': ['who','what','when']})df#    A         B    C     D# 0  7  0.704021  foo   who# 1  8  0.264025  bar  what# 2  9  0.230671  baz  whendf_numerics_only = df.select_dtypes(include=np.number)df_numerics_only#    A         B# 0  7  0.704021# 1  8  0.264025# 2  9  0.230671colnames_numerics_only = df.select_dtypes(include=np.number).columns.tolist()colnames_numerics_only# ['A', 'B']

You can use the undocumented function _get_numeric_data() to filter only numeric columns:

df._get_numeric_data()

Example:

In [32]: dataOut[32]:   A  B0  1  s1  2  s2  3  s3  4  sIn [33]: data._get_numeric_data()Out[33]:   A0  11  22  33  4

Note that this is a "private method" (i.e., an implementation detail) and is subject to change or total removal in the future. Use with caution.