drcjar

Let's make an Asthma Choropleth using open data, ogr2ogr, folium and pandas (and indirectly leaflet.js, d3.js, GeoJSON, open street maps and moar) and talk about using gist and blocks..

0. get UK Asthma data http://customer.instantatlas.com/INHALE/dataviews/ for this example I use dataView12_17.csv

1. get some CCG map boundaries

   wget 'https://geoportal.statistics.gov.uk/Docs/Boundaries/Clinical_commissioning_groups_(Eng)_Apr_2013_Boundaries_(Generalised_Clipped).zip'
   

2. make CCG map boundaries into GeoJSON format

drcjar

import nltk

with open('sample.txt', 'r') as f:
    sample = f.read()
     
sentences = nltk.sent_tokenize(sample)
tokenized_sentences = [nltk.word_tokenize(sentence) for sentence in sentences]
tagged_sentences = [nltk.pos_tag(sentence) for sentence in tokenized_sentences]
chunked_sentences = nltk.batch_ne_chunk(tagged_sentences, binary=True)