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Parse messy tabular data in various formats

Project description

Tabular data as published on the web is often not well formatted and structured. Messytables tries to detect and fix errors in the data. Typical examples include:

  • Finding the header of a table when there are explanations and text fragments in the first few rows of the table.
  • Guessing the type of columns in CSV data.

This library provides data structures and some heuristics to fix these problems and read a wide number of different tabular abominations.

See the full documentation at:

Project details

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