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Mapping location of air quality sensing in India

In this notebook, I'll show a quick example of how to use Folium (which internally uses LeafletJS) for visualising the location of air quality monitors in India. The purpose of this notebook is eductional in nature.

Standard Imports





In [1]:



    


import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
%matplotlib inline

Downloading data from OpenAQ for 2018-04-06





In [2]:



    


!wget --no-check-certificate https://openaq-data.s3.amazonaws.com/2018-04-06.csv -P /Users/nipun/Downloads/



    


















    






--2018-06-21 18:13:34--  https://openaq-data.s3.amazonaws.com/2018-04-06.csv
Resolving openaq-data.s3.amazonaws.com (openaq-data.s3.amazonaws.com)... 52.216.83.40
Connecting to openaq-data.s3.amazonaws.com (openaq-data.s3.amazonaws.com)|52.216.83.40|:443... connected.
WARNING: cannot verify openaq-data.s3.amazonaws.com's certificate, issued by ‘CN=DigiCert Baltimore CA-2 G2,OU=www.digicert.com,O=DigiCert Inc,C=US’:
  Unable to locally verify the issuer's authority.
HTTP request sent, awaiting response... 200 OK
Length: 133839107 (128M) [text/csv]
Saving to: ‘/Users/nipun/Downloads/2018-04-06.csv’

2018-04-06.csv      100%[===================>] 127.64M  1.29MB/s    in 3m 25s  

2018-06-21 18:17:02 (637 KB/s) - ‘/Users/nipun/Downloads/2018-04-06.csv’ saved [133839107/133839107]


















In [3]:



    


import pandas as pd
df = pd.read_csv("/Users/nipun/Downloads/2018-04-06.csv")
df = df[(df.country=='IN')&(df.parameter=='pm25')].dropna().groupby("location").mean()



    











In [4]:



    


df



    


















    
Out[4]:











  
    

      
      value
      latitude
      longitude
    

    

      location
      
      
      
    

  
  
    

      Adarsh Nagar, Jaipur - RSPCB
      79.916667
      26.902909
      75.836853
    

    

      Anand Kala Kshetram, Rajamahendravaram - APPCB
      42.750000
      16.987287
      81.736318
    

    

      Ardhali Bazar, Varanasi - UPPCB
      103.666667
      25.350599
      82.908307
    

    

      Asanol Court Area, Asanol - WBPCB
      56.833333
      23.685297
      86.945968
    

    

      Ashok Nagar, Udaipur - RSPCB
      114.750000
      24.588617
      73.632140
    

    

      Bandra, Mumbai - MPCB
      60.000000
      19.041847
      72.865513
    

    

      Bhopal Chauraha, Dewas - MPPCB
      159.416667
      22.968259
      76.064118
    

    

      Bollaram Industrial Area, Hyderabad - TSPCB
      62.400000
      17.540891
      78.358528
    

    

      Burari Crossing, New Delhi - IMD
      245.583333
      28.725650
      77.201157
    

    

      CRRI Mathura Road, New Delhi - IMD
      265.666667
      28.551200
      77.273574
    

    

      Central School, Lucknow - CPCB
      116.166667
      26.882100
      80.930275
    

    

      Central University, Hyderabad - TSPCB
      66.500000
      17.460103
      78.334361
    

    

      Chandrapur, Chandrapur - MPCB
      68.000000
      19.645324
      77.634523
    

    

      Civil Line, Jalandhar - PPCB
      135.833333
      31.321907
      75.578914
    

    

      Collectorate, Jodhpur - RSPCB
      321.750000
      26.268249
      73.019385
    

    

      DTU, New Delhi - CPCB
      214.333333
      28.750050
      77.111261
    

    

      GM Office, Brajrajnagar - OSPCB
      97.166667
      21.800500
      83.839698
    

    

      GVM Corporation, Visakhapatnam - APPCB
      57.416667
      17.720000
      83.300000
    

    

      Gangapur Road, Nashik - MPCB
      127.750000
      20.007328
      73.776243
    

    

      Golden Temple, Amritsar - PPCB
      83.000000
      31.620000
      74.876512
    

    

      ICRISAT Patancheru, Hyderabad - TSPCB
      69.166667
      17.434236
      78.417032
    

    

      IDA Pashamylaram, Hyderabad - TSPCB
      66.083333
      17.531689
      78.218939
    

    

      IGI Airport Terminal - 3, New Delhi - IMD
      130.666667
      28.562776
      77.118005
    

    

      IGSC Planetarium Complex, Patna - BSPCB
      134.833333
      25.594100
      85.137600
    

    

      IHBAS, Dilshad Garden,New Delhi - CPCB
      212.583333
      28.680275
      77.201157
    

    

      IIT, Chennai - CPCB
      37.333333
      13.005219
      80.239812
    

    

      ITO, New Delhi - CPCB
      220.500000
      28.631694
      77.249439
    

    

      Indira Colony Vistar, Pali - RSPCB
      206.250000
      25.771061
      73.340227
    

    

      Karve Road Pune, Pune - MPCB
      138.416667
      18.501174
      73.816553
    

    

      Lajpat Nagar, Moradabad - UPPCB
      105.800000
      28.825341
      78.721301
    

    

      ...
      ...
      ...
      ...
    

    

      Punjab Agricultural University, Ludhiana - PPCB
      82.666667
      30.902800
      75.808600
    

    

      Pusa, New Delhi - IMD
      112.000000
      28.610304
      77.099694
    

    

      R K Puram, New Delhi - DPCC
      103.600000
      28.564610
      77.167010
    

    

      RIICO Ind. Area III, Bhiwadi, Rajasthan - RSPCB
      340.500000
      28.194909
      76.862296
    

    

      RIMT University, Mandi Gobindgarh - PPCB
      132.750000
      30.649961
      76.331442
    

    

      Sanathnagar, Hyderabad - TSPCB
      90.333333
      17.455946
      78.433215
    

    

      Sanjay Palace, Agra - UPPCB
      166.666667
      27.198658
      78.005981
    

    

      Secretariat, Amaravati - APPCB
      47.200000
      16.515083
      80.518167
    

    

      Sector - 125, Noida, UP - UPPCB
      84.400000
      28.544761
      77.323126
    

    

      Sector - 62, Noida, UP - IMD
      154.416667
      28.624548
      77.357710
    

    

      Sector- 16A, Faridabad, Haryana - HSPCB
      264.250000
      28.408842
      77.309908
    

    

      Sector-2 Industrial Area, Pithampur - MPPCB
      101.166667
      22.624758
      75.675238
    

    

      Sector-6, Panchkula - HSPCB
      96.416667
      30.705778
      76.853181
    

    

      Sector-D Industrial Area, Mandideep - MPPCB
      125.416667
      23.108440
      77.511428
    

    

      Shadipur, New Delhi - CPCB
      213.833333
      28.651478
      77.147311
    

    

      Shastri Nagar, Jaipur - RSPCB
      100.083333
      26.950293
      75.730943
    

    

      Shrinath Puram, Kota - RSPCB
      120.916667
      25.143890
      75.821256
    

    

      Sirifort, New Delhi - CPCB
      222.250000
      28.550425
      77.215938
    

    

      Talkatora District Industries Center, Lucknow - CPCB
      163.833333
      26.833997
      80.891736
    

    

      Tirumala, Tirupati - APPCB
      52.833333
      13.670000
      79.350000
    

    

      US Diplomatic Post: Chennai
      19.958333
      13.087840
      80.278470
    

    

      US Diplomatic Post: Hyderabad
      55.458333
      17.384050
      78.456360
    

    

      US Diplomatic Post: Kolkata
      48.458333
      22.562630
      88.363040
    

    

      US Diplomatic Post: Mumbai
      -165.083333
      19.072830
      72.882610
    

    

      US Diplomatic Post: New Delhi
      46.625000
      28.635760
      77.224450
    

    

      Vasundhara, Ghaziabad, UP - UPPCB
      223.333333
      28.660335
      77.357256
    

    

      Vikas Sadan, Gurgaon, Haryana - HSPCB
      280.250000
      28.450124
      77.026305
    

    

      Vindhyachal STPS, Singrauli - MPPCB
      144.000000
      24.108970
      82.645580
    

    

      Ward-32 Bapupara, Siliguri - WBPCB
      195.000000
      26.688305
      88.412668
    

    

      Zoo Park, Hyderabad - TSPCB
      82.500000
      17.349694
      78.451437
    

  



79 rows × 3 columns

Downloading World GeoJson file





In [6]:



    


!wget --no-check-certificate https://raw.githubusercontent.com/python-visualization/folium/master/examples/data/world-countries.json



    


















    






--2018-06-21 18:18:42--  https://raw.githubusercontent.com/python-visualization/folium/master/examples/data/world-countries.json
Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 151.101.36.133
Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|151.101.36.133|:443... connected.
WARNING: cannot verify raw.githubusercontent.com's certificate, issued by ‘CN=DigiCert SHA2 High Assurance Server CA,OU=www.digicert.com,O=DigiCert Inc,C=US’:
  Unable to locally verify the issuer's authority.
HTTP request sent, awaiting response... 200 OK
Length: 252515 (247K) [text/plain]
Saving to: ‘world-countries.json’

world-countries.jso 100%[===================>] 246.60K   161KB/s    in 1.5s    

2018-06-21 18:18:45 (161 KB/s) - ‘world-countries.json’ saved [252515/252515]

Creating india.json correspdonding to Indian data





In [7]:



    


import json
e = json.load(open('world-countries.json','r'))
json.dump(e['features'][73], open('india.json','w'))



    











In [8]:



    


import folium

folium_map = folium.Map(width = '60%',height=800,location=[20, 77],
                        zoom_start=5,
                        tiles="Stamen Terrain",min_lat=7, max_lat=35, min_lon=73, max_lon=90)
for x in df.iterrows():
    name = x[0]
    lat, lon = x[1]['latitude'], x[1]['longitude']
    folium.CircleMarker([lat, lon], radius=5, color='#000000',fill_color='#D3D3D3' , fill_opacity=1).add_to(folium_map)

folium.GeoJson('india.json').add_to(folium_map)
folium_map



    


















    
Out[8]:

There you go!

Content source: lesley2958/lesley2958.github.io

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