numerizer

A Python module to convert natural language numerics into ints and floats. This is a port of the Ruby gem numerizer

Numerizer has been tested on Python 3.9, 3.10 and 3.11.

Installation

The numerizer library can be installed from PyPI as follows:

$ pip install numerizer

Usage

>>>fromnumerizerimportnumerize>>>numerize('forty two')
'42'>>>numerize('forty-two')
'42'>>>numerize('four hundred and sixty two')
'462'>>>numerize('one fifty')
'150'>>>numerize('twelve hundred')
'1200'>>>numerize('twenty one thousand four hundred and seventy three')
'21473'>>>numerize('one million two hundred and fifty thousand and seven')
'1250007'>>>numerize('one billion and one')
'1000000001'>>>numerize('nine and three quarters')
'9.75'>>>numerize('platform nine and three quarters')
'platform 9.75'

Using the SpaCy extension

Since version 0.2, numerizer is available as a SpaCy extension.

Any named entities of a quantitative nature within a SpaCy document can be numerized as follows:

>>>fromspacyimportload>>>nlp=load('en_core_web_sm') # or load any other spaCy model>>>doc=nlp('The projected revenue for the next quarter is over two million dollars.')
>>>doc._.numerize()
{thenextquarter: 'the next 1/4', overtwomilliondollars: 'over 2000000 dollars'}

Users can specify which entity types are to be numerized, by using the labels argument in the extension function, as follows:

>>>doc._.numerize(labels=['MONEY']) # only numerize entities of type 'MONEY'
{overtwomilliondollars: 'over 2000000 dollars'}

The extension is available for tokens and spans as well.

>>>two_million=doc[-4:-2] # span corresponding to "two million">>>two_million._.numerize()
'2000000'>>>quarter=doc[6] # token corresponding to "quarter">>>quarter._.numerized'1/4'

Extras

For R users, a wrapper library has been developed by @amrrs. Try it out here.