ABHISHEK SHARMA abhishek-shrm
abhishek-shrm
/ folium-tutorial-14.py
Created
April 21, 2020 12:28
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| india_geojson.plot() |
abhishek-shrm
/ folium-tutorial-15.py
Created
April 21, 2020 12:32
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| df_covid.isnull().sum() |
abhishek-shrm
/ folium-tutorial-16.py
Created
April 21, 2020 12:33
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| df_covid.dtypes |
abhishek-shrm
/ folium-tutorial-17.py
Last active
June 4, 2020 04:19
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| df_covid['Date']=pd.to_datetime(df_covid['Date']).apply(lambda x: x - pd.DateOffset(days=1)) |
abhishek-shrm
/ folium-tutorial-18.py
Created
April 21, 2020 12:36
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| df_covid['Name of State / UT'].unique() |
abhishek-shrm
/ folium-tutorial-19.py
Last active
June 4, 2020 04:21
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| df_covid['Name of State / UT']=df_covid['Name of State / UT'].apply(lambda x: re.sub('Union Territory of ','',x)) | |
| df_covid['Name of State / UT'].replace('Telengana','Telangana',inplace=True) | |
| df_covid['Name of State / UT'].replace('Dadar Nagar Haveli','Dadra and Nagar Haveli',inplace=True) |
abhishek-shrm
/ folium-tutorial-20.py
Created
April 21, 2020 12:38
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| 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', |
abhishek-shrm
/ folium-tutorial-21.py
Created
April 21, 2020 12:39
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| df_covid['Active Cases']=df_covid['Total Confirmed cases']-(df_covid['Cured/Discharged/Migrated']+df_covid['Death']) | |
| df_covid.head() |
abhishek-shrm
/ folium-tutorial-22.py
Last active
April 21, 2020 12:45
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| bins=np.linspace(min(df_covid['Active Cases']),max(df_covid['Active Cases']),11) | |
| bins |
abhishek-shrm
/ folium-tutorial-23.py
Created
April 21, 2020 12:46
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| # Coloring states and UTs with active COVID-19 cases | |
| df_covid['color']=pd.cut(df_covid['Active Cases'],bins,labels=['#FFEBEB','#F8D2D4','#F2B9BE','#EBA1A8','#E58892','#DE6F7C','#D85766','#D13E50','#CB253A','#C50D24'],include_lowest=False) | |
| # Coloring states and UTs with no active cases but previously had | |
| df_covid['color'].replace(np.nan,'#32CD32',inplace=True) |