Extract PDF Table to DataFrame Using Python Convert PDF to CSV in Jupyter Notebook
Want to extract tables or text from a PDF using Python?
In this step-by-step tutorial, I’ll show you how to use PyPDF2 and pdfplumber in Jupyter Notebook to extract data from PDF files and convert that data into a Pandas DataFrame that you can export to a CSV.
Perfect for data analysts, data scientists, and developers working with PDF reports, invoices, or scanned files!
🔍 What You’ll Learn :
• How to read PDF files using PyPDF2 and pdfplumber
• How to extract tabular data from a PDF
• How to convert extracted tables into a clean DataFrame
• How to export PDF data to a CSV file
📌 Tools Used :
• Python
• Jupyter Notebook
• PyPDF2
• pdfplumber
• pandas
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⏳ Timestamps ⏳
00:00 Introduction
01:14: Upload PDF file into Jupyter Notebook
02:11 Create a new workbook in Jupyter Notebook
02:25 Step 1: Install Required Libraries
03:36 Step 2: Import necessary Libraries
04:03 Define the path to read the PDF in Jupyter Notebook.
04:40 Step 3: Read PDF with PyPDF2
07:28 Step 4: Read the PDF with pdfplumber for the table.
09:42 Extract table
10:36 Step 5: Convert to Dataframe
11:57 Step 6: Save the dataset to a CSV file or xlsx file
13:18 Download the CSV or xlsx to your computer.
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