#!/usr/bin/env python
# coding: utf-8

# In[34]:


import pandas as pd, json, numpy as np
import matplotlib.pyplot as plt
get_ipython().run_line_magic('matplotlib', 'inline')


# In[35]:


from pygeocoder import Geocoder
apik='AIzaSyDybC2OroTE_XDJTuxjKruxFpby5VDhEGk'


# In[73]:


locations=json.loads(file('locations_hu.json','r').read())


# In[74]:


mdf_dest=pd.read_json(json.loads(file('mdf_hu_dest.json','r').read()))
mdf_arrv=pd.read_json(json.loads(file('mdf_hu_arrv.json','r').read()))


# In[75]:


citysave_dest=json.loads(file('citysave_hu_dest.json','r').read())
citysave_arrv=json.loads(file('citysave_hu_arrv.json','r').read())


# In[76]:


mdf_dest['ID']=mdf_dest['From']
mdf_dest.head()


# In[77]:


mdf_arrv['ID']=mdf_arrv['To']
mdf_arrv.head()


# In[78]:


mdf=pd.concat([mdf_dest,mdf_arrv])


# In[79]:


len(mdf_dest)


# In[80]:


len(mdf_arrv)


# In[81]:


mdf


# In[82]:


mdg=mdf.set_index(['ID','City','Airport','Airline'])


# In[83]:


k=mdg.loc['BUD'].loc['Frankfurt'].loc['FRA']
testurl=u'https://www.airportia.com/hungary/budapest-liszt-ferenc-international-airport/departures/20170318'
k[k['Date']==testurl]


# In[84]:


k=mdg.loc['BUD'].loc['Frankfurt'].loc['FRA']
testurl=u'https://www.airportia.com/hungary/budapest-liszt-ferenc-international-airport/arrivals/20170318'
k[k['Date']==testurl]


# In[85]:


k=mdg.loc['BUD'].loc['Frankfurt'].loc['FRA']
for i in range(11,25):
    testurl=u'https://www.airportia.com/hungary/budapest-liszt-ferenc-international-airport/departures/201703'+str(i)
    print 'BUD-FRA March',i, 'departures',len(k[k['Date']==testurl]),
    testurl=u'https://www.airportia.com/hungary/budapest-liszt-ferenc-international-airport/arrivals/201703'+str(i)
    print 'arrivals', len(k[k['Date']==testurl])


# In[88]:


len(k)/14


# `mdg` checks out with source

# In[89]:


flights={}
minn=1.0 #want to see minimum 1 flight in the past 2 weeks
for i in mdg.index.get_level_values(0).unique():
    #2 weeks downloaded. want to get weekly freq. but multi by 2 dept+arrv
    d=4.0
    if i not in flights:flights[i]={}
    for j in mdg.loc[i].index.get_level_values(0).unique():
        if len(mdg.loc[i].loc[j])>minn: #minimum 1 flights required in this period at least once every 2 weeks
            if j not in flights[i]:flights[i][j]={'airports':{},'7freq':0}
            flights[i][j]['7freq']=len(mdg.loc[i].loc[j])/d 
            for k in mdg.loc[i].loc[j].index.get_level_values(0).unique():
                if len(mdg.loc[i].loc[j].loc[k])>minn:
                    if k not in flights[i][j]['airports']:flights[i][j]['airports'][k]={'airlines':{},'7freq':0}
                    flights[i][j]['airports'][k]['7freq']=len(mdg.loc[i].loc[j].loc[k])/d
                    for l in mdg.loc[i].loc[j].loc[k].index.get_level_values(0).unique():
                        try:
                            if len(mdg.loc[i].loc[j].loc[k].loc[l])>minn: 
                                if l not in flights[i][j]['airports'][k]['airlines']:flights[i][j]['airports'][k]['airlines'][l]={'7freq':0}
                                flights[i][j]['airports'][k]['airlines'][l]['7freq']=len(mdg.loc[i].loc[j].loc[k].loc[l])/d
                        except:pass


# In[90]:


file("flights_hu.json",'w').write(json.dumps(flights))