Post Office example

names1.txt

Post Office - High Littleton
Post Office Pilton Outreach Services
Town Street Post Office
post office St Thomas

Full example is here https://gist.github.com/maZahaca/a54046a4cc7ab27f9d06751b89aa7446

Basically need to find out some algorithm or better library, to get such results:
Post Office: 16999
Post: 17934
Office: 16999
Tesco: 7300
...

Currently the main problem is detection of sentences.

Here is a code for doing this for words:

from textblob import TextBlob
import operator

title_file = open("names.txt", 'r')
blob = TextBlob(title_file.read())
list = sorted(blob.word_counts.items(), key=operator.itemgetter(1))
print list

Here are some restrictions:

• only groups, which contains more than 1 name
• only groups, which contains only textual data
• it could contain sentences, from several words
• only input should be - a list of names