animationdataload.py

import requests
import pandas
import json
import plotly.express as px

districts_daily = requests.get('https://api.covid19india.org/v4/timeseries.json')
districts_daily = districts_daily.text
districts_daily = json.loads(districts_daily)

dfs = []

for key in districts_daily.keys():
    totalconfirmed= []
    totaldeceased = []
    totalrecovered = []
    totaltested = []
    deltaconfirmed = []
    deltadeceased = []
    deltarecovered = []
    deltatested = []
    dates = []
    states = []
    for date in districts_daily[key]['dates']:
        deltas = districts_daily[key]['dates'][date].get('delta')
        totals = districts_daily[key]['dates'][date].get('total')
        if not deltas is None:
            deltaconfirmed.append(deltas.get('confirmed'))
            deltadeceased.append(deltas.get('deceased'))
            deltarecovered.append(deltas.get('recovered'))
            deltatested.append(deltas.get('tested'))
        else:
            deltaconfirmed.append(None)
            deltadeceased.append(None)
            deltarecovered.append(None)
            deltatested.append(None)
        if not totals is None:
            totalconfirmed.append(totals.get('confirmed'))
            totaldeceased.append(totals.get('deceased'))
            totalrecovered.append(totals.get('recovered'))
            totaltested.append(totals.get('tested'))
        else:
            totalconfirmed.append(None)
            totaldeceased.append(None)
            totalrecovered.append(None)
            totaltested.append(None)
        states.append(key)
        dates.append(date)
    df = pandas.DataFrame({'deltaconfirmed': deltaconfirmed, 'deltadeceased': deltadeceased, 'deltarecovered': deltarecovered,
                       'totalconfirmed': totalconfirmed, 'totaldeceased': totaldeceased, 'totalrecovered': totalrecovered,
                       'deltatested':deltatested, 'totaltested':totaltested,'date': dates, 'state': states})
    df = df.fillna(method='ffill')
    df = df.fillna(0)
    dfs.append(df)

data = pandas.concat(dfs, ignore_index=True)
data['date']= pandas.to_datetime(data['date'], format = '%Y/%m/%d')
data = data[data['state']!='UN']
data = data[data['state']!='TT']
data = data.sort_values(by='date')
data2 =data[data['date']>data.groupby('state').min().max()['date']]
statenames = {
    'HR': 'Haryana', 'DN':'Dadra and Nagar Haveli', 'AS':'Assam', 'TG':'Telangana', 'KL':'Kerala', 
    'AR':'Arunachal Pradesh', 'TN':'Tamil Nadu', 'TR':'Tripura', 'KA':'Karnataka',
    'GA':'Goa', 'JK':'Jammu and Kashmir',
    'AP':'Andhra Pradesh', 'UP':'Uttar Pradesh',
    'GJ':'Gujarat', 'JH':'Jharkhand', 
    'LA':'Ladakh', 'MH':'Maharashtra', 'SK':'Sikkim', 
    'UT':'Uttaranchal', 'BR':'Bihar', 'PY':'Puducherry', 'CT':'Chhattisgarh',
    'MP':'Madhya Pradesh', 'WB':'West Bengal', 'HP':'Himachal Pradesh',
    'AN':'Andaman and Nicobar', 'PB':'Punjab', 'OR':'Odisha', 'ML':'Meghalaya', 'MZ':'Mizoram', 
    'CH':'Chandigarh', 'DL':'Delhi', 'MN':'Manipur',
    'RJ':'Rajasthan', 'NL':'Nagaland'  
    }

data2['state'] = data2['state'].apply(lambda x:statenames[x])