From 73498a9d6730b2673e422699c41711a61b084793 Mon Sep 17 00:00:00 2001 From: Vinayak Mehta Date: Sat, 5 Jan 2019 02:12:14 +0530 Subject: [PATCH] Update README --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 1d89c30..3f6013f 100644 --- a/README.md +++ b/README.md @@ -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! @@ -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).