How to Get Columns of Numeric Datatype from DataFrame?

Pandas DataFrame – Select Columns of Numeric Datatype

To select columns that are only of numeric datatype from a Pandas DataFrame, call DataFrame.select_dtypes() method and pass np.number or 'number' as argument for include parameter. The DataFrame.select_dtypes() method for this given argument returns a subset of this DataFrame with only numeric columns.

Syntax of select_datatypes()

The syntax to call select_datatypes() method of a DataFrame is

DataFrame.select_dtypes(include=None, exclude=None)

Examples

1. Select numeric columns from DataFrame

In this example, we have created a DataFrame and we shall get only those columns which are numeric using DataFrame.select_dtypes() method.

import pandas as pd

df = pd.DataFrame(
    [['abc', 22, 22.6],
    ['xyz', 25, 23.2],
    ['pqr', 31, 30.5]],
    columns=['name', 'age', 'bmi'])

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

Output

   age   bmi
0   22  22.6
1   25  23.2
2   31  30.5

Only the columns with numeric datatype are selected from this DataFrame.

Summary

In this tutorial of Python Examples, we learned how to select only the numeric columns of DataFrame using DataFrame.select_dtypes() method.