Working with PDFs that contain tables, reports, or invoice data? Manually copying that information into spreadsheets is slow, error-prone, and just plain frustrating. Fortunately, there's a smarter way: you can convert PDF to CSV in Python automatically — making your data easy to analyze, import, or automate.
In this guide, you’ll learn how to use Python for PDF to CSV conversion by directly extracting tables with Spire.PDF for Python — a pure Python library that doesn’t require any external tools.
✅ No Adobe or third-party tools required
✅ High-accuracy table recognition
✅ Ideal for structured data workflows
In this guide, we’ll cover:
- Convert PDF to CSV in Python Using Table Extraction
- Related Use Cases
- Why Use Spire.PDF for PDF to CSV Conversion in Python?
- Frequently Asked Questions
Convert PDF to CSV in Python Using Table Extraction
The best way to convert PDF to CSV using Python is by extracting tables directly — no need for intermediate formats like Excel. This method is fast, clean, and highly effective for documents with structured data such as invoices, bank statements, or reports. It gives you usable CSV output with minimal code and high accuracy, making it ideal for automation and data analysis workflows.
Step 1: Install Spire.PDF for Python
Before writing code, make sure to install the required library. You can install Spire.PDF for Python via pip:
pip install spire.pdfYou can also install Free Spire.PDF for Python if you're working on smaller tasks:
pip install spire.pdf.freeStep 2: Python Code — Extract Table from PDF and Save as CSV
- Python
from spire.pdf import PdfDocument, PdfTableExtractor
import csv
import os
# Load the PDF document
pdf = PdfDocument()
pdf.LoadFromFile("Sample.pdf")
# Create a table extractor
extractor = PdfTableExtractor(pdf)
# Ensure output directory exists
os.makedirs("output/Tables", exist_ok=True)
# Loop through each page in the PDF
for page_index in range(pdf.Pages.Count):
# Extract tables on the current page
tables = extractor.ExtractTable(page_index)
for table_index, table in enumerate(tables):
table_data = []
# Extract all rows and columns
for row in range(table.GetRowCount()):
row_data = []
for col in range(table.GetColumnCount()):
# Get cleaned cell text
cell_text = table.GetText(row, col).replace("\n", "").strip()
row_data.append(cell_text)
table_data.append(row_data)
# Write the table to a CSV file
output_path = os.path.join("output", "Tables", f"Page{page_index + 1}-Table{table_index + 1}.csv")
with open(output_path, "w", newline="", encoding="utf-8") as csvfile:
writer = csv.writer(csvfile)
writer.writerows(table_data)
# Release PDF resources
pdf.Dispose()The conversion result:
What is PdfTableExtractor?
PdfTableExtractor is a utility class provided by Spire.PDF for Python that detects and extracts table structures from PDF pages. Unlike plain text extraction, it maintains the row-column alignment of tabular data, making it ideal for converting PDF tables to CSV with clean structure.
Best for:
- PDFs with structured tabular data
- Automated Python PDF to CSV conversion
- Fast Python-based data workflows
Relate Article: How to Convert PDFs to Excel XLSX Files with Python
Related Use Cases
If your PDF doesn't contain traditional tables — such as when it's formatted as paragraphs, key-value pairs, or scanned as an image — the following approaches can help you convert such PDFs to CSV using Python effectively:
Useful when data is in paragraph or report form — format it into table-like CSV using Python logic.
Perfect for image-based PDFs — use OCR to detect and export tables to CSV.
Why Choose Spire.PDF for Python?
Spire.PDF for Python is a robust PDF SDK tailored for developers. Whether you're building automated reports, analytics tools, or ETL pipelines — it just works.
Key Benefits:
- Accurate Table Recognition
Smartly extracts structured data from tables
- Pure Python, No Adobe Needed
Lightweight and dependency-free
- Multi-Format Support
Also supports conversion to text, images, Excel, and more
Frequently Asked Questions
Can I convert PDF to CSV using Python?
Yes, you can convert PDF to CSV in Python using Spire.PDF. It supports both direct table extraction to CSV and an optional workflow that converts PDFs to Excel first. No Adobe Acrobat or third-party tools are required.
What's the best way to extract tables from PDFs in Python?
The most efficient way is using Spire.PDF’s PdfTableExtractor class. It automatically detects tables on each page and lets you export structured data to CSV with just a few lines of Python code — ideal for invoices, reports, and automated processing.
Why would I convert PDF to Excel before CSV?
You might convert PDF to Excel first if the layout is complex or needs manual review. This gives you more control over formatting and cleanup before saving as CSV, but it's slower than direct extraction and not recommended for automation workflows.
Does Spire.PDF work without Adobe Acrobat?
Yes. Spire.PDF for Python is a 100% standalone library that doesn’t rely on Adobe Acrobat or any external software. It's a pure Python solution for converting, extracting, and manipulating PDF content programmatically.
Conclusion
Converting PDF to CSV in Python doesn’t have to be a hassle. With Spire.PDF for Python, you can:
- Automatically extract structured tables to CSV
- Build seamless, automated workflows in Python
- Handle both native PDFs and scanned ones (with OCR)
Get a Free License
Spire.PDF for Python offers a free edition suitable for basic tasks. If you need access to more features, you can also apply for a free license for evaluation use. Simply submit a request, and a license key will be sent to your email after approval.
