Extract PDF Tables in Minutes with Camelot: A Simple Python Guide

Extracting tables from PDF files is often painful, but the Python library Camelot can do it with just a few lines of code.

Camelot reads PDF files, converts tables to pandas DataFrames, and supports exporting to CSV, JSON, Excel, HTML, or SQLite.

Camelot是什么

According to the project description, Camelot is a Python tool for extracting table data from PDF files.

代码示例

The project provides a PDF file (shown in the image) and demonstrates how to extract the table 2‑1.

import camelot

tables = camelot.read_pdf('foo.pdf')  # similar to pandas reading a CSV
print(tables[0].df)  # get a pandas DataFrame!

tables.export('foo.csv', f='csv', compress=True)  # export to csv, json, excel, html, sqlite

tables[0].to_csv('foo.csv')  # also can export to json, excel, html, sqlite

print(tables)  # <TableList n=1>
print(tables[0])  # <Table shape=(7, 7)>
print(tables[0].parsing_report)
# {'accuracy': 99.02, 'whitespace': 12.24, 'order': 1, 'page': 1}

The output handles merged cells by inserting empty rows, which is a reliable approach.

安装方法

Three installation methods are provided:

Conda (simplest): conda install -c conda-forge camelot-py Pip with OpenCV dependencies: pip install camelot-py[cv] Clone the repository and install from source:

git clone https://www.github.com/camelot-dev/camelot
cd camelot
pip install ".[cv]"

These methods allow users to quickly set up Camelot and start extracting tables from PDFs.