Let’s say we have the following DataFrame:

   A
0  1
1  2
2  3
3  4
4  5

The DataFrame has a single column named “A”. Let’s say we want to add two columns “B” and “C” in the DataFrame, such that the DataFrame becomes like this:

   A   B   C
0  1   6  11
1  2   7  12
2  3   8  13
3  4   9  14
4  5  10  15

In this article, we will discuss how to add multiple columns in a DataFrame using the pandas Python library.

We can use the following Python code to add multiple columns in a DataFrame:

import pandas
import numpy

df = pandas.DataFrame([1, 2, 3, 4, 5], columns=["A"])
print("DataFrame before adding columns: \n", df)

# df[numpy.array(["B", "C"])] = pandas.DataFrame([[6, 11], [7, 12], [8, 13], [9, 14], [10, 15]])

df[numpy.array(["B", "C"])] = numpy.array([[6, 11], [7, 12], [8, 13], [9, 14], [10, 15]])
print("DataFrame after adding columns: \n", df)

Firstly, we are creating the DataFrame df that has one column A. After that, we are using the following Python statement …