Python - Compare two csv file - based on Column - pandas

Question

I am trying to compare two CSV files, most of the time it will have same data but order of data will not be the same. Eg
csv file1
AAA,111,A1A1
BBB,222,B2B2
CCC,333,C3C3
CSV File2
CCC,333,C3C3
BBB,212,B2B2
AAA,111,A1A1
so I want to use third column as Primary key to compare other values. Report the difference. Is this possible to do it in Robotframework or Panda?

Answer 1

If you are making use of robotframework you need to do the following,
install robotframework-csvlib
Use Built-in Collections
Input from your question
csv file1
AAA,111,A1A1
BBB,222,B2B2
CCC,333,C3C3
csv file2
CCC,333,C3C3
BBB,212,B2B2
AAA,111,A1A1
My Solution
In the below approach, we are first reading csv into list of lists for both csv files and then comparing all the list of list items by making use of Collections KW List Should Contain Sub List, here, notice that we are passing an argument "values=True" which compares the value as well.
Code that compares 2 csv files
*** Settings ***
Library CSVLib
Library Collections
*** Test Cases ***
Test CSV
${list1}= read csv as list csv1.csv
log to console ${list1}
${list2}= read csv as list csv2.csv
log to console ${list2}
List Should Contain Sub List ${list1} ${list2} values=True
OUTPUT
(rf1) C:\Users\kgurupra>robot s1.robot
==============================================================================
S1
==============================================================================
Test CSV .[['C1,C2,C3'], ['AAA,111,A1A1'], ['BBB,222,B2B2'], ['CCC,333,C3C3']]
..[['C1,C2,C3'], ['CCC,333,C3C3'], ['BBB,212,B2B2'], ['AAA,111,A1A1']]
Test CSV | FAIL |
Following values were not found from first list: ['BBB,212,B2B2']
------------------------------------------------------------------------------
S1 | FAIL |
1 critical test, 0 passed, 1 failed
1 test total, 0 passed, 1 failed
==============================================================================
Output: C:\Users\kgurupra\output.xml
Log: C:\Users\kgurupra\log.html
Report: C:\Users\kgurupra\report.html

Answer 2

Assuming you've imported your CSV files as pandas DataFrames you can do the following to merge the two while retaining fundamental differences:
df = csv1.merge(csv2, on='<insert name primary key column here>',how='outer')
Adding the suffixes option allows you to more clearly differentiate between identically named columns from each file:
df = csv1.merge(csv2, on='<insert name>',how='outer',suffixes=['_csv1','_csv2'])
After that it depends on what kind of differences you are looking to spot but perhaps a starting point is:
df['difference_1'] = df['column1_csv1'] == df['column1_csv2']
this will create a boolean column which indicates True if observations are the same and False otherwise.
But there are nearly endless options for comparison.