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Vinayak Mehta 2019-01-05 02:12:14 +05:30
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@ -21,7 +21,7 @@
>>> tables = camelot.read_pdf('foo.pdf')
>>> tables
<TableList n=1>
>>> tables.export('foo.csv', f='csv', compress=True) # json, excel, html
>>> tables.export('foo.csv', f='csv', compress=True) # json, excel, html, sqlite
>>> tables[0]
<Table shape=(7, 7)>
>>> tables[0].parsing_report
@ -31,7 +31,7 @@
'order': 1,
'page': 1
}
>>> tables[0].to_csv('foo.csv') # to_json, to_excel, to_html
>>> tables[0].to_csv('foo.csv') # to_json, to_excel, to_html, to_sqlite
>>> tables[0].df # get a pandas DataFrame!
</pre>
@ -53,7 +53,7 @@ There's a [command-line interface](https://camelot-py.readthedocs.io/en/master/u
- **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. (This is important since everything in the real world, including PDF table extraction, is fuzzy.)
- *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 seamlessly integrates into [ETL and data analysis workflows](https://gist.github.com/vinayak-mehta/e5949f7c2410a0e12f25d3682dc9e873).
- **Export** to multiple formats, including JSON, Excel and HTML.
- **Export** to multiple formats, including JSON, Excel, HTML and Sqlite.
See [comparison with other PDF table extraction libraries and tools](https://github.com/socialcopsdev/camelot/wiki/Comparison-with-other-PDF-Table-Extraction-libraries-and-tools).