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Compare two Pandas DataFrames on values

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by vsasikalabe dot icon Updated: Feb 28, 2023

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A Data Frame is used to keep data in a tabular format, and it is a two-dimensional structure made of rows and columns. It is flexible to store various types of tabular data. Many operations and calculations can be done on the row and column labels. When dealing with pandas' data frames, we need to determine if two data frames are equivalent. The result should be true if both data frame values are the same. Otherwise, it is set to be false. 


The duplicated() method compares two different Data Frames. It returns True if they are equal in both shape and content. Otherwise False. For that, we have to create two data frames with data values. And also, the compare() method in pandas shows the differences between the two Data Frames. It compares two data frames, row-wise and column-wise, and displays the differences side by side. The compare method can only compare Data Frames with exact dimensions and identical row and column labels of the same shape. Use the merge() function to merge Pandas Data Frame. We can assign the indicator value to True or False. Use indicator= True to check which data frame has a specific record. 

The tuple() function is used in Python to create a tuple or convert an iterable-like list to a tuple. A tuple is a sequence of values that is immutable (cannot be changed). Tuples are typically used for different purposes, similar to lists. If they contain only strings and numbers, Tuples can be used as keys. tuples cannot be used as a key if a tuple contains any mutable object, directly or indirectly. 


Here is an example of how to compare two Pandas Data frames on Values: 

Preview of the output that you will get on running this code from your IDE.

Code

In this solution we used pandas library of python.

How to compare two Pandas DataFrames on values?

PythondotLines of Code : 25dotLicense : Strong Copyleft (CC BY-SA 4.0)

Dependent Libraries : 
import pandas as pd

df1 = pd.DataFrame([[-37.3794288,175.6697856],
                    [-37.0334148,174.8680204],
                    [-41.173852,174.981931]],
                   columns=['Long', 'Lat'])

df2 = pd.DataFrame([[-37.0334148,174.8680204],
                    [-37.5575605,175.1584622],
                    [-37.0334148,174.8680204]],
                   columns=['Long', 'Lat'])


df1['Result'] = [tuple(i) in set(map(tuple, df2.values)) for i in df1.values]

#         Long         Lat  Result
# 0 -37.379429  175.669786   False
# 1 -37.033415  174.868020    True
# 2 -41.173852  174.981931   False

df = pd.merge(df1, df2, indicator=True, how='left').\
              drop_duplicates().rename(columns={'_merge': 'Result'})

df['Result'] = df['Result'].map({'left_only': False, 'both': True})

Instructions

Follow the steps carefully to get the output easily.

  1. Download and install PyCharm on your Computer
  2. Create new Python file on your IDE.
  3. Copy the snippet using the 'copy' and paste it in your file.
  4. Install pandas on your IDE(Any of your favorite IDE).
  5. Run the file to generate the output.


I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.


I found this code snippet by searching for ' Compare two Pandas DataFrames on values' in kandi. You can try any such use case!

Environment Tested

I tested this solution in the following versions. Be mindful of changes when working with other versions.

  1. The solution is created in PyCharm 2022.3.
  2. The solution is tested on Python 3.11.1
  3. Pandas version-1.5.2.


Using this solution, we are able to Compare two Pandas DataFrames on values with simple steps. This process also facilities an easy way to use, hassle-free method to create a hands-on working version of code which would help us to Compare two Pandas DataFrames on values.

Dependent Library

pandasby pandas-dev

Python doticonstar image 38689 doticonVersion:v2.0.2doticon
License: Permissive (BSD-3-Clause)

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

Support
    Quality
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            pandasby pandas-dev

            Python doticon star image 38689 doticonVersion:v2.0.2doticon License: Permissive (BSD-3-Clause)

            Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
            Support
              Quality
                Security
                  License
                    Reuse

                      If you do not have pandas library that is required to run this code, you can install it by clicking on the above link.

                      You can search for any dependent library on kandi like pandas.

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