Convert HDFC Bank Credit Card statements from PDF to Excel

statement-to-excel.py

# This script is designed to convert bank statements from pdf to excel.
#
# It has been tweaked on HDFC Bank Credit Card statements,
# but in theory you can use it on any PDF document.
#
# The script depends on camelot-py,
# which can be installed using pip
#
# pip install "camelot-py[cv]"


import os
import argparse
import camelot
import pandas as pd
from collections import defaultdict


def extract_df(path, password=None):
    # The default values from pdfminer are M = 2.0, W = 0.1 and L = 0.5
    laparams = {'char_margin': 2.0, 'word_margin': 0.2, 'line_margin': 1.0}

    # Extract all tables using the lattice algorithm
    lattice_tables = camelot.read_pdf(path, password=password, 
        pages='all', flavor='lattice', line_scale=50, layout_kwargs=laparams)

    # Extract bounding boxes
    regions = defaultdict(list)
    for table in lattice_tables:
        bbox = [table._bbox[i] for i in [0, 3, 2, 1]]
        regions[table.page].append(bbox)

    df = pd.DataFrame()

    # Extract tables using the stream algorithm
    for page, boxes in regions.items():
        areas = [','.join([str(int(x)) for x in box]) for box in boxes]
        stream_tables = camelot.read_pdf(path, password=password, pages=str(page),
            flavor='stream', table_areas=areas, row_tol=5, layout_kwargs=laparams)
        dataframes = [table.df for table in stream_tables]
        dataframes = pd.concat(dataframes)
        df = df.append(dataframes)
    
    return df


def main(args):
    for file_name in os.listdir(args.in_dir):
        root, ext = os.path.splitext(file_name)
        if ext.lower() != '.pdf':
            continue
        pdf_path = os.path.join(args.in_dir, file_name)
        print(f'Processing: {pdf_path}')
        df = extract_df(pdf_path, args.password)
        excel_name = root + '.xlsx'
        excel_path = os.path.join(args.out_dir, excel_name)
        df.to_excel(excel_path)
        print(f'Processed : {excel_path}')
        

if __name__ == '__main__':
    parser = argparse.ArgumentParser()
    parser.add_argument('--in-dir', type=str, required=True, help='directory to read statement PDFs from.')
    parser.add_argument('--out-dir', type=str, required=True, help='directory to store statement XLSX to.')
    parser.add_argument('--password', type=str, default=None, help='password for the statement PDF.')
    args = parser.parse_args()

    main(args)

@pushkaryadav
thanks on sharing the excel codes..can you change the excel formula for Cell E2 (For Narration/Description)
Its the same as for date

@malharlakdawala
Updated the formula.

These formulas were supposed to be temporary but fortunately they are still working after 6 months and I am yet to see an error/incorrect output. If I ever change the formula, aka make the formulas more flexible I'll share them here.

One good example of making the sheet better is in the formula of B2. Instead of looking for the " cr" in the whole sentence, I should rather look for " cr" using the RIGHT function.

Alternative formula for cell B2
=NOT(RIGHT($A2,3)=" Cr")

Regards.

@sethia
Thank you for the suggestion but IIRC, I did try tabula or something similar, it was too much work and didn't really work. My current setup is much easier and user friendly, at least for me.
So currently, I have no need to look for further options.

Bank statement is already being updated daily since it is a necessity. So a combined statement won't help much as I'll have to get in touch with the bank once again and they are not working at their full potential for many months now. It took multiple reminder phone calls and three weeks just to switch our banking e-statement from monthly to daily.

Thanks for this @nikhilweee

For windows, I modified the code as below and ran it on Jupyter. I just directly mentioned the filepaths in the code, instead of feeding through the function, which was causing the issues. You can change the actual paths as per your own system. I used a sample folder on the desktop to check if this works. Thanks @nikhilweee :)

import os
import argparse
import camelot
import pandas as pd
from collections import defaultdict


def extract_df(path, password=None):
    # The default values from pdfminer are M = 2.0, W = 0.1 and L = 0.5
    laparams = {'char_margin': 2.0, 'word_margin': 0.2, 'line_margin': 1.0}

    # Extract all tables using the lattice algorithm
    lattice_tables = camelot.read_pdf(path, password=password, 
        pages='all', flavor='lattice', line_scale=50, layout_kwargs=laparams)

    # Extract bounding boxes
    regions = defaultdict(list)
    for table in lattice_tables:
        bbox = [table._bbox[i] for i in [0, 3, 2, 1]]
        regions[table.page].append(bbox)

    df = pd.DataFrame()

    # Extract tables using the stream algorithm
    for page, boxes in regions.items():
        areas = [','.join([str(int(x)) for x in box]) for box in boxes]
        stream_tables = camelot.read_pdf(path, password=password, pages=str(page),
            flavor='stream', table_areas=areas, row_tol=5, layout_kwargs=laparams)
        dataframes = [table.df for table in stream_tables]
        dataframes = pd.concat(dataframes)
        df = df.append(dataframes)
    
    return df


pdf_path = 'C:\\Users\\<Your_name>\\Desktop\\HDFCCredit\\HDFCJan.PDF'
print(f'Processing: {pdf_path}')
df = extract_df(pdf_path)
excel_name = 'export.xlsx'
excel_path = 'C:\\Users\\<Your_name>\\Desktop\\HDFCCredit\\export.xlsx'
df.to_excel(excel_path)
print(f'Processed : {excel_path}')

@cstambay glad that I could be of help :)

I had to install Ghostscript along with camelot-py[cv] after that it worked perfectly fine - Thank you @nikhilweee

@simplyrahul I got the same error
ValueError: min() arg is an empty sequence
in my Windows system. After some debugging, I found a fix by changing the _text_bbox(t_bbox) method in camelot-py's file 'stream.py' as below. It works for me now. Hope it helps.

`

def _text_bbox(t_bbox):
"""Returns bounding box for the text present on a page.

    Parameters
    ----------
    t_bbox : dict
        Dict with two keys 'horizontal' and 'vertical' with lists of
        LTTextLineHorizontals and LTTextLineVerticals respectively.

    Returns
    -------
    text_bbox : tuple
        Tuple (x0, y0, x1, y1) in pdf coordinate space.

    """
    xmin = 0
    ymin = 0
    xmax = 0
    ymax = 0
    if len([t.x0 for direction in t_bbox for t in t_bbox[direction]])>0:
        xmin = min([t.x0 for direction in t_bbox for t in t_bbox[direction]])
        ymin = min([t.y0 for direction in t_bbox for t in t_bbox[direction]])
        xmax = max([t.x1 for direction in t_bbox for t in t_bbox[direction]])
        ymax = max([t.y1 for direction in t_bbox for t in t_bbox[direction]])
    text_bbox = (xmin, ymin, xmax, ymax)
    return text_bbox

`

Thanks a lot, @nikhilweee for this! Been using it from the last three years.

While running on a new system, got the following error:

PyPDF2.errors.DeprecationError: PdfFileReader is deprecated and was removed in PyPDF2 3.0.0. Use PdfReader instead

Refer camelot-dev/camelot#339

What worked for me

python3.8 -m pip uninstall PyPDF2
python3.8 -m pip install PyPDF2~=2.0

The code is not working, kindly check...

Looks like the method append has been removed from the pandas module a long time ago

$ python3 ~/scripts/statement-to-excel.py --in-dir . --out-dir .
Processing: ./2024-04.PDF
Traceback (most recent call last):
  File "/Users/nowalekar/scripts/statement-to-excel.py", line 68, in <module>
    main(args)
  File "/Users/nowalekar/scripts/statement-to-excel.py", line 54, in main
    df = extract_df(pdf_path, args.password)
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/nowalekar/scripts/statement-to-excel.py", line 42, in extract_df
    df = df.append(dataframes)
         ^^^^^^^^^
  File "/Users/nowalekar/scripts/hdfc-cc-statement/lib/python3.12/site-packages/pandas/core/generic.py", line 6299, in __getattr__
    return object.__getattribute__(self, name)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
AttributeError: 'DataFrame' object has no attribute 'append'. Did you mean: '_append'?

Fix on line #42:
df = pd.concat([df, dataframes])