Skip to main content

Extracts data from tables

Project description

TableDataExtractor

Extracts data from tables with complicated structures, by standardizing the table.

Documentation

https://cambridgemolecularengineering-tabledataextractor.readthedocs-hosted.com/en/latest/

License

The MIT License (MIT)

Copyright © 2019 Juraj Mavračić and contributors

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Acknowledgements

Core algorithms used and modified in TableDataExtractor have originally been developed by Embley et al. This is the MIPS (Minimum Indexing Point Search) algorithm that is used to find the row/column headers and the data region, as well as algorithms for prefixing header cells. Also, some of the examples in this documentation are based on examples from Embley et al:

Embley, D.W., Krishnamoorthy, M.S., Nagy, G., and Seth, S. (2016) Converting heterogeneous statistical tables on the web to searchable databases. *Int. J. Doc. Anal. Recognit.*, *19* (2), 119–138.

Algorithms for duplicating spanning cells and extending headers, that are used in TableDataExtractor, have been developed by Nagy and Seth:

Nagy, G., and Seth, S. (2017) Table headers: An entrance to the data mine. *Proc. - Int. Conf. Pattern Recognit.*, 4065–4070.

The algorithm for converting html files to Numpy arrays has been modified from John Rico:

John Ricco, (2017) Using Python to scrape HTML tables with merged cells, https://johnricco.github.io/2017/04/04/python-html/

Please cite these works where appropriate.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

tabledataextractor-1.5.11.tar.gz (127.5 kB view details)

Uploaded Source

File details

Details for the file tabledataextractor-1.5.11.tar.gz.

File metadata

  • Download URL: tabledataextractor-1.5.11.tar.gz
  • Upload date:
  • Size: 127.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.15 tqdm/4.62.3 importlib-metadata/4.10.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.8.12

File hashes

Hashes for tabledataextractor-1.5.11.tar.gz
Algorithm Hash digest
SHA256 bff1558cb7deba95ad93df8bc410d7448d9fa5cd11e3630a06f07e9c9efec469
MD5 704e96e75c6937f2c4258c7c6c658d8f
BLAKE2b-256 da03d18df170a0c206694b9792a21b8209a7cf195ba50c33717be95c9e6814ef

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page