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Simple wrapper for tabula-java, read tables from PDF into DataFrame

Project description

tabula-py

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tabula-py is a simple Python wrapper of tabula-java, which can read tables in a PDF. You can read tables from a PDF and convert them into a pandas DataFrame. tabula-py also enables you to convert a PDF file into a CSV, a TSV or a JSON file.

You can see the example notebook and try it on Google Colab, or we highly recommend reading our documentation, especially the FAQ section.

tabula-py example

Requirements

  • Java 8+
  • Python 3.8+

OS

I confirmed working on macOS and Ubuntu. But some people confirm it works on Windows 10. See also the documentation for the detailed installation for Windows 10.

Usage

Install

Ensure you have a Java runtime and set the PATH for it.

pip install tabula-py

Example

tabula-py enables you to extract tables from a PDF into a DataFrame, or a JSON. It can also extract tables from a PDF and save the file as a CSV, a TSV, or a JSON.  

import tabula

# Read pdf into list of DataFrame
dfs = tabula.read_pdf("test.pdf", pages='all')

# Read remote pdf into list of DataFrame
dfs2 = tabula.read_pdf("https://github.com/tabulapdf/tabula-java/raw/master/src/test/resources/technology/tabula/arabic.pdf")

# convert PDF into CSV file
tabula.convert_into("test.pdf", "output.csv", output_format="csv", pages='all')

# convert all PDFs in a directory
tabula.convert_into_by_batch("input_directory", output_format='csv', pages='all')

See an example notebook for more details. I also recommend reading the tutorial article written by @aegis4048, and another tutorial written by @tdpetrou.

Contributing

Interested in helping out? I'd love to have your help!

You can help by:

  • Reporting a bug.
  • Adding or editing documentation.
  • Contributing code via a Pull Request. See also for the contribution
  • Write a blog post or spread the word about tabula-py to people who might be able to benefit from using it.

Contributors

Another support

You can also support our continued work on tabula-py with a donation on GitHub Sponsors or Patreon.

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