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How to Compare Two Columns of Pandas DataFrame?

Given a Pandas DataFrame, we have to compare its two columns. By Pranit Sharma Last updated : September 23, 2023

Pandas is a special tool that allows us to perform complex manipulations of data effectively and efficiently. Inside pandas, we mostly deal with a dataset in the form of DataFrame. DataFrames are 2-dimensional data structures in pandas. DataFrames consists of rows, columns, and the data.

Problem statement

Given a Pandas DataFrame, we have to compare its two columns.

Comparing Two Columns of Pandas DataFrame

Comparing columns is important as we need to understand the difference between the columns. For this purpose, we will use a method called numpy.where(), it acts like a conditional statement that checks the condition defined inside it and then compares the columns.

Syntax

numpy.where(condition, [x, y, ]/)

import pandas as pd

Let us understand with the help of an example,

Python Program to Compare Two Columns of Pandas DataFrame

# Importing pandas 
import pandas as pd

# Importing numpy package
import numpy as np

# Create a DataFrame
df = pd.DataFrame({
    'A':[39,40,32,45,89,102293],
    'B':[40,39,22,54,22,0],
    'C':[42,44,20,49,30,110],
    'D':[30,34,43,56,44,86],
    'E':[76,67,45,56,55,45]
})

# Display original DataFrame
print("Orignal DataFrame:\n",df,"\n")

# Comparing two columns
df['result'] = np.where((df['A'] <= df['B']) & (
    df['A'] <= df['C']), df['A'], np.nan)

# Display result
print("Result:\n",df)

Output

The output of the above program is:

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