标签：#statement

If you've ever tried converting a bank statement PDF to CSV and ended up with a jumbled mess of merged cells, missing rows, or split transaction descriptions — you're not alone. This is one of the most common data pain points for accountants, bookkeepers, and anyone who does their own finances. In this post, I'll walk through why this happens, what the right approach looks like, and how to get clean, analysis-ready CSV output from any bank statement. Why Bank Statement PDFs Are So Hard to Parse Bank statements aren't structured documents — they're designed for printing, not data extraction. Here's what generic converters run into: Merged cells : PDF renderers often group date + description + amount into a single visual block. Naive converters pick one cell boundary and split it wrong. Multi-line transactions : A single transaction entry (especially with memos) can span 2–3 lines in the PDF, but gets split into separate rows in the spreadsheet. Negative vs. positive amounts : Debit/credit columns vary by bank.Chase uses a single "Amount" column with negatives for debits. BoA uses two separate columns. A generic converter treats them identically and produces wrong signs. Running balance drift : If even one row is misaligned, every balance figure below it is off. Method 1: Manual Copy-Paste (What You're Probably Doing Now) The baseline. Open the PDF, select all, paste into Excel, then spend 30 minutes fixing column alignment. Pros: Free, no tools required. Cons: Slow (20–40 minutes per statement), error-prone, completely unscalable if you have multiple accounts or months to process. Method 2: Python + pdfplumber For developers who want a scriptable solution: import pdfplumber import csv with pdfplumber . open ( " statement.pdf " ) as pdf : rows = [] for page in pdf . pages : table = page . extract_table () if table : rows . extend ( table ) with open ( " output.csv " , " w " , newline = "" ) as f : writer = csv . writer ( f ) writer . writerows ( rows ) This works reas