In [30]:
import pandas as pd, json, numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
In [31]:
flights=json.loads(file('flights_hu.json','r').read())
locations=json.loads(file('locations_hu.json','r').read())
citysave_dest=json.loads(file('citysave_hu_dest.json','r').read())
citysave_arrv=json.loads(file('citysave_hu_arrv.json','r').read())
#example output format
data1a=json.loads(file('data1a.json','r').read())
data2a=json.loads(file('data2a.json','r').read())
In [32]:
cc={
'DEB':u'Debrecen',
'BUD':u'Budapest'
}
In [33]:
citysave={}
for i in list(citysave_dest)+list(citysave_arrv):
if i in citysave_dest:
citysave[i]=citysave_dest[i]
else:
citysave[i]=citysave_arrv[i]
In [34]:
citysave['Cluj-Napoca']['coords']=[46.5385862, 24.5514392]
In [35]:
newdata={}
apconv={}
for g in citysave:
k=g+'('+str(citysave[g]['coords'][0])+', '+str(citysave[g]['coords'][1])+')'
apconv[g]=k
if k not in newdata: newdata[k]={}
newdata[k]['coords']=citysave[g]['coords']
newdata[k]['country']=citysave[g]['country']
newdata[k]['count']=0
In [36]:
for c in flights:
for airport in flights[c]:
k=apconv[airport]
newdata[k]['count']+=flights[c][airport]['7freq']
if c not in newdata[k]:
newdata[k][c]={"count":0}
newdata[k][c]['count']+=flights[c][airport]['7freq']
newdata[k][c]['airports']=flights[c][airport]['airports']
In [37]:
#clean up
for i in list(newdata.keys()):
if newdata[i]['count']==0: newdata.pop(i);
In [38]:
F=[]
for j in newdata:
for i in newdata[j]:
if i not in {'country','count','coords'}:
for k in newdata[j][i]['airports']:
for m in newdata[j][i]['airports'][k]['airlines']:
if 'cargo' not in m.lower():
F.append({'to':j[:j.find('(')],'from':cc[i],'country':newdata[j]['country'],'ap':j[:j.find('(')]+' '+str(k),'al':m,u'weekly flights':np.round(newdata[j][i]['airports'][k]['airlines'][m]['7freq'],1)})
#tests
F.append({'to':j[:j.find('(')],'from':cc[i],'country':newdata[j]['country'],'ap':j[:j.find('(')]+' '+str(k),'al':u'Total',u'weekly flights':0})
F.append({'to':j[:j.find('(')],'from':cc[i],'country':newdata[j]['country'],'ap':u'Total','al':m,u'weekly flights':0})
F.append({'to':j[:j.find('(')],'from':cc[i],'country':u'Total','ap':j[:j.find('(')]+' '+str(k),'al':m,u'weekly flights':0})
F.append({'to':j[:j.find('(')],'from':u'Total','country':newdata[j]['country'],'ap':j[:j.find('(')]+' '+str(k),'al':m,u'weekly flights':0})
F.append({'to':u'Total','from':cc[i],'country':newdata[j]['country'],'ap':j[:j.find('(')]+' '+str(k),'al':m,u'weekly flights':0})
In [39]:
file("f_hu.json",'w').write(json.dumps(F))
In [40]:
F=[]
typ=u'Hungary flights'
for j in newdata:
for i in newdata[j]:
if i not in {'country','count','coords'}:
for k in newdata[j][i]['airports']:
for m in newdata[j][i]['airports'][k]['airlines']:
if 'cargo' not in m.lower():
F.append({'type':typ,'to':j[:j.find('(')],'from':cc[i],'country':newdata[j]['country'],'ap':j[:j.find('(')]+' '+str(k),'al':m,u'weekly flights':np.round(newdata[j][i]['airports'][k]['airlines'][m]['7freq'],1)})
#tests
F.append({'type':typ,'to':j[:j.find('(')],'from':cc[i],'country':newdata[j]['country'],'ap':j[:j.find('(')]+' '+str(k),'al':u'Total',u'weekly flights':0})
F.append({'type':typ,'to':j[:j.find('(')],'from':cc[i],'country':newdata[j]['country'],'ap':u'Total','al':m,u'weekly flights':0})
F.append({'type':typ,'to':j[:j.find('(')],'from':cc[i],'country':u'Total','ap':j[:j.find('(')]+' '+str(k),'al':m,u'weekly flights':0})
F.append({'type':typ,'to':j[:j.find('(')],'from':u'Total','country':newdata[j]['country'],'ap':j[:j.find('(')]+' '+str(k),'al':m,u'weekly flights':0})
F.append({'type':typ,'to':u'Total','from':cc[i],'country':newdata[j]['country'],'ap':j[:j.find('(')]+' '+str(k),'al':m,u'weekly flights':0})
In [41]:
file("g_hu.json",'w').write(json.dumps(F))
In [42]:
s=0
for j in ["DEB","BUD"]:
newdata[cc[j]+'('+str(locations[j][0])+', '+str(locations[j][1])+')']={j:{'airports': {j: {u'7freq': s,
u'airlines': {u'Airport': {u'7freq': s}}}},
'count': s},
'coords': locations[j],
'count': s,
'country': u'Hungary'}
In [43]:
file("newdata1a_hu.json",'w').write(json.dumps(newdata))
data2a
In [44]:
gountrygeo=json.load(file('gountrygeo.json','r'))
In [45]:
gountrygeo["Canada"]=[61, -29]
gountrygeo["United States"]=[57, -29]
gountrygeo["Romania"]=[46.052612, 24.954499]
gountrygeo["Other"]=[58, 44]
gountrygeo["None"]=[0, 0]
gountrygeo[None]=[0, 0]
In [46]:
from pygeocoder import Geocoder
apik='AIzaSyDybC2OroTE_XDJTuxjKruxFpby5VDhEGk'
In [47]:
for c in list(set(citysave[g]['country'] for g in citysave)):
if c not in gountrygeo:
print c
gountrygeo[c]=Geocoder(apik).geocode(c)[0].coordinates
In [48]:
file("gountrygeo.json",'w').write(json.dumps(gountrygeo))
In [49]:
newdatar={}
for g in citysave:
k=citysave[g]['country']
if k not in newdatar: newdatar[k]={}
newdatar[k]['coords']=gountrygeo[k]
newdatar[k]['count']=0
In [50]:
for c in flights:
for airport in flights[c]:
k=citysave[airport]['country']
newdatar[k]['count']+=flights[c][airport]['7freq']
if c not in newdatar[k]:
newdatar[k][c]={"count":0,'cities':{}}
newdatar[k][c]['count']+=flights[c][airport]['7freq']
#if airport not in newdatar['cities'][k][c]['cities']:
newdatar[k][c]['cities'][airport]=flights[c][airport]
In [51]:
file("newdata2a_hu.json",'w').write(json.dumps(newdatar))
colors
In [52]:
file("cities_hu.json",'w').write(json.dumps(cc))
In [53]:
order=['BUD','DEB']
In [54]:
ss={
'DEB':'#1c9099',
'BUD':'#fd8d3c'
}
In [55]:
file("colors_hu.json",'w').write(json.dumps(ss))
In [56]:
file("citycoords_hu.json",'w').write(json.dumps({i:locations[i] for i in locations if i in cc}))
In [57]:
file("cityorder_hu.json",'w').write(json.dumps(order))