I have hundreds of Excel files containing financial transactions (e.g., stocks, mutual funds, etc.) in varying formats. Each file can contain one or more tables, and the tables are located at different positions with respect to different brokers like zerodha, groww, etc.
My goal is to train a deep learning model that can automatically identify and extract the relevant table(s) from any given Excel file.
This is the data: https://drive.google.com/drive/folders/1YixwjLg2ZskRXMI5WMjns5kD1Ujfpphd?usp=sharing
Like in image, pdf files we train on a no. of files and then new format is given, the model can give the required data with precision and accuracy even if the format is changed. The challenge is to perform this on excel files.
I tried annotating the excel files with the coordinates of location of table and type of data in each cell within that range but didn't get promising results.
