fuzzytable 0.9a0

Read tables from messy spreadsheets.

Overview

fuzzytable is a set of tools for extracting tabular data out of messy spreadsheets.

This library was developed to meet the needs of projects relying on spreadsheet data that has been handled by many people. Headers are often missing or mispelled. The data is incorrectly formatted. The table is on the wrong worksheet or you don't know the correct spreadsheet name. Etc...

fuzzytable allows you to quickly extract that data instead of arduously QC'ing the data ahead of time. After extraction, you can query the FuzzyTable attributes to e.g. determine which fields were found and how closely the desired header matches the actual header.

Installation

pip install fuzzytable

Example Usage

Here's a light-hearted demo. To read this messy file using, say, the csv module, we'd have to first:

• Delete rows 1 and 2.
• Delete columns A and B.
• Rename the headers.

A	B	C	D	E
These	are	not	the	droids
you	are	looking	for.	He
can	go	c o l o r	first name	GivenName
about	his	Gold	C	3PO
business	.	Blue	R2	D2

Let's instead leverage the FuzzyTable class.

>>> from fuzzytable import FuzzyTable

>>> droids = FuzzyTable(
...     path='droids.csv',
...     fields=['first_name', 'last_name', 'color'],
...     approximate_match=True,
...     min_ratio=.3
... )

Now let's play with the data we've extracted.

>>> droids['color']
['Gold', 'Blue']

>>> for droid in droids.records:
...     print(f"{droid['first_name']}-{droid['last_name']} is {droid['color']}.")
C-3PO is Gold.
R2-D2 is Blue.

>>> droids.fields['first_name'].col_num
3

>>> droids.sheet.header_row
2

Links

• Documentation (tutorials, etc): fuzzytable.readthedocs.io
• PyPI: pypi.org/project/fuzzytable
• github: github.com/jonathanchukinas/fuzzytable
• Submit issues: github.com/jonathanchukinas/fuzzytable/issues

Supported Formats

• Excel (.xlsx, .xlsm, .xltx, .xltm)
• csv (.csv)

Basically, anything that can be read by the openpyxl or csv modules.