Creating Bank Reconciliation from 2 csv files

Question

Hello. I'm a student and want to automate the process of bank recon from to csv files using pandas library. How is that?

Answer 1

Removed mfd mark as Christian Jayson Bajaro elaborated on his question 👌

Answer 2

Why don't you put some of that sample data into a python code in code playground, so the task would be more clear. A couple of lines would be enough. You can normally import a csv file with pandas. Here you cannot upload the csv, but you can simulate the same if you create dataframe from python lists.

Answer 3

Christian Jayson Bajaro
I imagine the data may look like this.
https://code.sololearn.com/cPC7dYHPvT3n/?ref=app
I will try this exercise too, I am a data wrangler myself too, so I am interested in learning more about pandas.
The answer should be somewhere here:
https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html

Answer 4

it is fine and a great idea

Answer 5

Hi,
Do you have any specific question about this? If you just want to announce your project, please use your personal activity feed.
Good luck with your endeavour, sounds interesting!

Answer 6

Hello 😊 sorry for that. What I mean was How to do that? Hehe. I'm just almost 3 weeks in python and started with an exercise to extract a specific data from a large string. Hehe. And I made it because of Pandas Library. Now the next exercise is having 2 csv files (Cashbook and Bank Records).
Maybe my 1st question now is:
How to match the check numbers from the 2 csv files and get the specific row with the matched check numbers then differenciate the amounts of the 2 matched datas?
also, only the rows with check numbers will be use to match because there are NoneType or None in Check Number column where I extracted using RegEx and Pandas.
Thank you in advance 😊

Answer 7

Hello there. I already did merge it. Thanks for sharing.
My problem now is their data types. They are in object types even the amounts. Whenever I try to get the difference, it causes TypeError. Cannot minus 'str' to 'str' or cannot convert object to float (if I try to convert to float)