import pandas as pd, numpy as np, json
metros=json.loads(open('metrosg.json','r').read())
years={}
for m in metros:
metro=metros[m]
for i in range(1830,2021):
if str(i) in metro['desc']:
years[m]=i
break
for m in metros:
if m not in years:
print(metros[m]['name'],m)
Hong Kong MTR https://www.metrolinemap.com/metro/hong-kong/ Bangkok Metro https://www.metrolinemap.com/metro/bangkok/ Copenhagen Metro https://www.metrolinemap.com/metro/copenhagen/ Toulouse Metro https://www.metrolinemap.com/metro/toulouse/ Philadelphia SEPTA and PATCO https://www.metrolinemap.com/metro/philadelphia/
years['https://www.metrolinemap.com/metro/hong-kong/']=1979
years['https://www.metrolinemap.com/metro/bangkok/']=2004
years['https://www.metrolinemap.com/metro/copenhagen/']=2002
years['https://www.metrolinemap.com/metro/toulouse/']=1993
years['https://www.metrolinemap.com/metro/philadelphia/']=1928
for m in metros:
metros[m]['year']=years[m]
#manuallly prettify names
metros['https://www.metrolinemap.com/metro/london/']['name']='London Underground'
metros['https://www.metrolinemap.com/metro/atlanta/']['name']='Atlanta MARTA'
metros['https://www.metrolinemap.com/metro/cleveland/']['name']='Cleveland RTA'
metros['https://www.metrolinemap.com/metro/boston/']['name']='Boston T'
metros['https://www.metrolinemap.com/metro/chicago/']['name']='Chicago L'
open('metrosy.json','w').write(json.dumps(metros))
6433711
import zipfile
zipfile.ZipFile('metrosy.zip', "w", zipfile.ZIP_DEFLATED).write('metrosy.json')