Python Pandas- Compare Two CSV files, based on that comparison update CSV file

Sometimes we need to compare 2 CSV and get a list of common rows or common columns, that is a very common requirement.

But sometimes we also need to compare CSV files and based one comparison need to update CSV file. In this example I am going to elaborate that, hope that will help others.

I got this requirement in “Reconciliation” module in one of my project, where One CSV I got from Bank where I can see all transactions happened in one day .

I have another csv where I have all transactions recorded in my database. So now we need to compare transaction with common id (Like transaction id ) and find out all transactions which are not present in our DB.

So let’s go

Now I have written one python class “csv_compare”.py

									
import pandas as pd

def read_compare():
    f1 = pd.read_csv('test1.csv')
    for index, row in f1.iterrows():
    	transaction_id=row['transaction_id']
    	search_status = find_and_match(transaction_id)
    	if search_status == True:
    		print('Matched')

   

def find_and_match(transaction_id):
    print(transaction_id)
    f2 = pd.read_csv('test2.csv')
    index = f2[f2['transaction_id'] == transaction_id]
    print(len(index.index.values))
    if len(index.index.values) > 0:
        status_col = 'status'
        f2 = f2.set_value(index.index.values[0], status_col,1)
        f2.to_csv('test2.csv', index=False)
        return True
    else:
        return False

In this class first I imported Pandas, then read 2 csv files and then I add one more column in first CSV (CSV1) name “status”. Fetching Each row of first CSV and If transaction id is present in CSV2 file then i Updated that row “Matched” in new column “status”

I have Runner class file “runner.py”

									
import csv_compare

csv_compare.read_compare()
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