Camelot is a Python library which makes it easy for anyone to extract tables from PDF files!
Here's how you can extract tables from PDF files. Check out the PDF used in this example, here.
>>> import camelot
>>> tables = camelot.read_pdf('foo.pdf')
>>> tables
<TableList n=1>
>>> tables.export('foo.csv', f='csv', compress=True) # json, excel, html
>>> tables[0]
<Table shape=(7, 7)>
>>> tables[0].parsing_report
{
'accuracy': 99.02,
'whitespace': 12.24,
'order': 1,
'page': 1
}
>>> tables[0].to_csv('foo.csv') # to_json, to_excel, to_html
>>> tables[0].df # get a pandas DataFrame!
| Cycle Name | KI (1/km) | Distance (mi) | Percent Fuel Savings | |||
|---|---|---|---|---|---|---|
| Improved Speed | Decreased Accel | Eliminate Stops | Decreased Idle | |||
| 2012_2 | 3.30 | 1.3 | 5.9% | 9.5% | 29.2% | 17.4% |
| 2145_1 | 0.68 | 11.2 | 2.4% | 0.1% | 9.5% | 2.7% |
| 4234_1 | 0.59 | 58.7 | 8.5% | 1.3% | 8.5% | 3.3% |
| 2032_2 | 0.17 | 57.8 | 21.7% | 0.3% | 2.7% | 1.2% |
| 4171_1 | 0.07 | 173.9 | 58.1% | 1.6% | 2.1% | 0.5% |
There's a command-line interface too!
Note: Camelot only works with text-based PDFs and not scanned documents. If you can click-and-drag to select text in your table in a PDF viewer, then your PDF is text-based.
- You are in control: Unlike other libraries and tools which either give a nice output or fail miserably (with no in-between), Camelot gives you the power to tweak table extraction. (Since everything in the real world, including PDF table extraction, is fuzzy.)
- Metrics: Bad tables can be discarded based on metrics like accuracy and whitespace, without ever having to manually look at each table.
- Each table is a pandas DataFrame, which enables seamless integration into ETL and data analysis workflows.
- Export to multiple formats, including json, excel and html.
See comparison with other PDF table extraction libraries and tools.
After installing the dependencies (tk and ghostscript), you can simply use pip to install Camelot:
$ pip install camelot-py
After installing the dependencies, clone the repo using:
$ git clone https://www.github.com/socialcopsdev/camelot
and install Camelot using pip:
$ cd camelot $ pip install .
Note: Use a virtualenv if you don't want to affect your global Python installation.
Great documentation is available at http://camelot-py.readthedocs.io/.
The Contributor's Guide has detailed information about contributing code, documentation, tests and more. We've included some basic information in this README.
You can check the latest sources with:
$ git clone https://www.github.com/socialcopsdev/camelot
You can install the development dependencies easily, using pip:
$ pip install camelot-py[dev]
After installation, you can run tests using:
$ python setup.py test
Camelot uses Semantic Versioning. For the available versions, see the tags on this repository.
This project is licensed under the MIT License, see the LICENSE file for details.