A Python script that pulls the tables out of your PDF reports, price lists or statements into Excel

Example result

python merge_sales.py --month 2026-10

2026-11-02 09:14:03 INFO  Folder: sales/2026-10, 9 files found
2026-11-02 09:14:03 INFO  shop-01.csv: 1,284 rows
2026-11-02 09:14:04 INFO  shop-02.xlsx: 967 rows
2026-11-02 09:14:04 WARN  shop-07.csv: 3 rows without a price skipped (lines 88, 412, 913)
2026-11-02 09:14:05 INFO  Done: 10,412 rows -> report-2026-10.xlsx (sheets "Sales" and "Totals")

[columns]
date = Date, Sale date, Day
product = Product, Item, Name
quantity = Qty, Quantity, Pcs
price = Price, Unit price

def read_shop_file(path: Path, columns: dict[str, list[str]]) -> pd.DataFrame:
    """Reads one shop's file and gives it the report's column names."""
    table = pd.read_excel(path) if path.suffix == ".xlsx" else pd.read_csv(path, encoding="utf-8-sig")
    renamed = {}
    for name, variants in columns.items():
        found = next((c for c in table.columns if c.strip() in variants), None)
        if found is None:
            raise ReportError(f"{path.name}: no column for '{name}' (looked for {', '.join(variants)})")
        renamed[found] = name
    table = table.rename(columns=renamed)[list(columns)]
    table["shop"] = path.stem
    return table

About this service

Supplier price lists, bank or marketplace reports and stock lists often come only as PDF, and copying their tables into Excel breaks the columns. This Python script reads the tables of your PDFs and writes them into Excel or CSV with the columns in place: it joins a table that runs over many pages, drops repeated header lines and page footers and, from Standard, turns 1 234,50 or (120.00) into real numbers and dates into dates. It is tuned to the layout of your files, so send one or two typical PDFs or the same layout with made-up figures. The PDF must contain real text, as most files saved from a program do; scans and photos of paper need text recognition, which is not included. You run the script yourself and check the totals.

What is included

• What you getA ZIP archive with the Python script, a README with step-by-step instructions and, from Standard, a settings file with column names and pages; the code is also shown on the order page.
• Tuned to your layoutBuilt and tried on the sample files you send
• Columns in placeOne row in the PDF is one row in Excel
• Many pages joinedA long table becomes one sheet without repeated headers
• Real numbersFrom Standard, amounts and dates you can sum and sort
• Readable codeWith comments, easy to adjust if the layout changes

How it works

1. 1
   SamplesYou send one or two typical PDFs and show the table you need
2. 2
   CodeWe write the script for that layout and the guide to running it
3. 3
   Try itYou run it on your files and check the totals against the PDF
4. 4
   ChangesYou ask for changes within your package and send any error message

What we need from you

One or two typical PDFs of the kind you get (or the same layout with made-up names and figures), which table on which pages you need, and the columns you want in Excel. How numbers are written in them (commas, spaces, minus signs or brackets) and the date format. Whether all your files share one layout or there are several kinds, roughly how many files you process, and your system: Windows, macOS or Linux.

We will ask you:

• What are the PDFs?
• Which columns do you need in Excel?
• Do all your files look the same?
• Where will it run?

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Questions and answers

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