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id_dict={'Andaman and Nicobar Islands': '0', | |
'Arunachal Pradesh': '1', | |
'Assam': '2', | |
'Bihar': '3', | |
'Chandigarh': '4', | |
'Chhattisgarh': '5', | |
'Dadra and Nagar Haveli': '6', | |
'Daman and Diu': '7', | |
'Goa': '8', | |
'Gujarat': '9', | |
'Haryana': '10', | |
'Himachal Pradesh': '11', | |
'Jharkhand': '12', | |
'Karnataka': '13', | |
'Kerala': '14', | |
'Lakshadweep': '15', | |
'Madhya Pradesh': '16', | |
'Maharashtra': '17', | |
'Manipur': '18', | |
'Meghalaya': '19', | |
'Mizoram': '20', | |
'Nagaland': '21', | |
'Delhi': '22', | |
'Puducherry': '23', | |
'Punjab': '24', | |
'Rajasthan': '25', | |
'Sikkim': '26', | |
'Tamil Nadu': '27', | |
'Telangana': '28', | |
'Tripura': '29', | |
'Uttar Pradesh': '30', | |
'Uttarakhand': '31', | |
'West Bengal': '32', | |
'Odisha': '33', | |
'Andhra Pradesh': '34', | |
'Jammu and Kashmir': '35', | |
'Ladakh': '36'} | |
# Creating IDs using the above dictionary | |
df_covid['state_id']=df_covid['Name of State / UT'].map(id_dict) |
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