Python BankFile Analysis

Version: 0.1

Note : sample file provided to test

How-to:

0. Extract BankFile_Analysis_Pack_v0.1.rar into a dedicated folder - see 'Release'

Note: Other Files are the source code.

1. Add your BankFile to the designated folder (Source).

   Note: There is currently no check to validate if the file fits with the parser. Please ensure that you provide the correct BankFile in the appropriate folder.

2. Delete the provided sample file.

3. Adjust categories as desired (Files in folder Resources).

   A) Config: "CategoriesDefinition.csv"

   This file contains unique IDs that will be used to categorize data.

   • Category 3: Investments should remain unchanged to ensure the related graph displays relevant data.

   • You can create your own categories, but they must follow the structure shown below (Categories 2 to 5 are optional):

     

   Fields:

   • IsExp: Set to 1 if this category is related to an expense.
   • Cat_20_30_50: Refers to the 50/30/20 budget (see here). Use 100% when it is an income.
   • AssetType: The type of asset when the category is for Category 3: Investments.

   B) Config: "WildcardsCategory.csv"

   In this file, you define patterns for words found in your BankFile details. When a matching pattern is detected, it will link to the appropriate category (as set up in CategoriesDefinition.csv). You need to provide an existing ID from CategoriesDefinition.csv.

   C) Config: "AbsoluteCategory.csv"

   This file is useful for categorizing specific transactions based on their unique PK_Hash (available in the exported CSV dataset). Transactions in AbsoluteCategory.csv will take precedence over those categorized through WildcardsCategory.csv.