• Overview About The Project:

  This project will help users to analyze their Paytm Wallet Statement. Exploratory Data Analysis(EDA) and Data Visualization has been done in the project files to help user understand how they made their transaction.

• Files Included In The Project:

  1. mainFunctions.ipynb: contains user defined functions(for performing EDA and Data Visualization).

  2. mainData.ipynb: contains code to display the dataframe of the Wallet Statement and to display number of activities done and some exploratory analysis.

  3. Money Sent.ipynb: contains code to explore the activity 'Money Sent'.

  4. Money Received.ipynb: contains code to explore the activity 'Money Received'.

  5. Added To Paytm Account.ipynb: contains code to explore activity 'Added To Paytm Account'.

  6. Paid For Order.ipynb: contains code to explore activity 'Paid For Order.ipynb'.

  7. Cashback Received.ipynb: contains code to explore activity 'Cashback Received'.

  8. Refunds For Order.ipynb: contains code to explore activity 'Refunds For Order'.

  9. Paytm_Wallet_Statement.csv: that's your Paytm Wallet Statement.

  10. README.md: file which you are reading right now.

• How To Run:

  1. Firstly, you have to rename your Wallet Statement file to 'Paytm_Wallet_Statement'(without the quote) and remember that your Wallet Statement file should be in csv format otherwise the code won't run.
  2. Then all you have to do is, open mainFunctions.ipynb file and run all the blocks in that file. The file contians all the function that are used in the data analysis of your Paytm Wallet Statement. So they must be run at the starting for the execution of the whole program.
  3. Then what you can do is go to mainData.ipynb file to see how the dataset prepared from your Wallet Statement file looks like. It's code will tell you what are the activities you have performed while making transactions. On the basis of those listed activities you can go to the respective ipynb file(activity and file names are the same) to see your transaction history and some data analysis which has been done.

NOTE: Github is not rendering the plotly graphs as of now and so to see the plots you have to follows the follwing thing:

Open the ipynb files hover over that circular sign and then click on the link. It will send you to another page where you can see the whole code and plots as well.

e.g.