Thermal Power Plants in India - An Interactive Visualization

import pandas as pd
sheet = 'Sheet1'
# Name of excel file sourced from www.globalenergymonitor.org
file_name = 'CPI.xlsx' 

# Conversion to Dataframe
dfs = pd.read_excel(file_name, sheet_name=sheet)
# Remove Duplicates and convert to list.
plantlist = dfs[dfs.columns[1]].drop_duplicates(keep='first', inplace=False).values.tolist()

# Number of Power Stations
len(plantlist)

# Sanity Check - First 11 plants
testList = namelist[0:10]

testList

# Importing the requests library 
import requests 
  
# Api-endpoint 
URL = "https://maps.googleapis.com/maps/api/geocode/json"

# Output json location with station name.
jso = pd.DataFrame(columns = ['location','json'])

# key = # Get key from Google Cloud 
for location in plantlist:
  
  # Defining a params dict for the parameters to be sent to the API 
  PARAMS = {'address':location,'key':key} 
  
  # Sending get request and saving the response as response object 
  r = requests.get(url = URL, params = PARAMS) 
  
  # Extracting data in json format 
  data = r.json() 
  
  # Appending Location to json output
  jso = jso.append(pd.Series([location,data], index=jso.columns), ignore_index=True)

# Output station name with location in Json.
jso

f = pd.DataFrame(columns = ['location', 'latitude', 'longitude'])

j = jso['json']
i = 0
for location in plantlist:
   # Extracting latitude, longitude and formatted address of the first matching location 
  if len(j[i]['results']) != 0  :
    latitude = j[i]['results'][0]['geometry']['location']['lat'] 
    longitude = j[i]['results'][0]['geometry']['location']['lng']
  else:
    latitude = ''
    longitude = ''

  f = f.append(pd.Series([location,latitude,longitude], index=f.columns), ignore_index=True)
  i = i + 1

# Final dataframe f with location, latitude and longitude
f

# Converting to .csv for further exploration and vizualization in Tableau.
f.to_csv('raw.csv')