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How to compare values in two Pandas Dataframes?

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  • Last Updated : 12 Jan, 2022

Let’s discuss how to compare values in the Pandas dataframe. Here are the steps for comparing values in two pandas Dataframes:

Step 1 Dataframe Creation: The dataframes for the two datasets can be created using the following code: 

Python3




import pandas as pd
 
# elements of first dataset
first_Set = {'Prod_1': ['Laptop', 'Mobile Phone',
                        'Desktop', 'LED'],
             'Price_1': [25000, 8000, 20000, 35000]
             }
 
# creation of Dataframe 1
df1 = pd.DataFrame(first_Set, columns=['Prod_1', 'Price_1'])
print(df1)
 
# elements of second dataset
second_Set = {'Prod_2': ['Laptop', 'Mobile Phone',
                         'Desktop', 'LED'],
              'Price_2': [25000, 10000, 15000, 30000]
              }
 
# creation of Dataframe 2
df2 = pd.DataFrame(second_Set, columns=['Prod_2', 'Price_2'])
print(df2)

Output:

pandas-comapre-value-2pandas-comapre-value-2

Step 2 Comparison of values: You need to import numpy for the successful execution of this step. Here is the general template to perform the comparison:

df1[‘new column for the comparison results’] = np.where(condition, ‘value if true’, ‘value if false’)

Example: After execution of this code, the new column with the name Price_Matching will be formed under df1. Columns result will be displayed according to the following conditions: 

  • If Price_1 is equal to Price_2, then assign the value of True
  • Otherwise, assign the value of False.

Python3




import numpy as np
 
# add the Price2 column from
# df2 to df1
df1['Price_2'] = df2['Price_2']
 
# create new column in df1 to
# check if prices match
df1['Price_Matching'] = np.where(df1['Price_1'] == df2['Price_2'],
                                 'True', 'False'
df1

Output:

pandas-comapre-value-3


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