Python: visualización de datos con la API de India de covid19

API (interfaz de programación de aplicaciones) es una interfaz informática que interactúa entre varios programas. 

JSON (Notación de objetos de JavaScript) es un formato ligero para almacenar y transportar datos. Se utiliza para enviar datos del servidor a la web.

Módulos requeridos: 

• matplotlib
• peticiones
• pandas
• json

Comandos para instalar módulos:

pip install matplotlib
pip install requests
pip install pandas

Pasos:

1. Importación de todos los módulos requeridos.
2. Llamar a la API y obtener datos JSON.
3. Obtener los datos del Distrito Sabio del Estado.
4. Visualización de datos.

La siguiente URL lo redirige a la API https://api.covid19india.org/state_district_wise.json

Importación de todos los módulos requeridos

#importing modules
import json
import requests
import pandas as pd
import matplotlib.pyplot as plt

Función para obtener datos JSON de API y visualización de datos

#storing the url in the form of string
url="https://api.covid19india.org/state_district_wise.json"
 
#function to get data from api
def casesData():
    #getting the json data by calling api
    data = ((requests.get(url)).json())
    states = []

Obtener nombres de estado disponibles en datos JSON

# getting statewise data
for state in states:
        f = (data[state]['districtData'])
# states data available in JSON Data
'''
0 State Unassigned
1 Andaman and Nicobar Islands
2 Andhra Pradesh
3 Arunachal Pradesh
4 Assam
5 Bihar
6 Chandigarh
7 Chhattisgarh
8 Delhi
9 Dadra and Nagar Haveli and Daman and Diu
10 Goa
11 Gujarat
12 Himachal Pradesh
13 Haryana
14 Jharkhand
15 Jammu and Kashmir
16 Karnataka
17 Kerala
18 Ladakh
19 Lakshadweep
20 Maharashtra
21 Meghalaya
22 Manipur
23 Madhya Pradesh
24 Mizoram
25 Nagaland
26 Odisha
27 Punjab
28 Puducherry
29 Rajasthan
30 Sikkim
31 Telangana
32 Tamil Nadu
33 Tripura
34 Uttar Pradesh
35 Uttarakhand
36 West Bengal
'''

Obtener los datos estatales

# getting statewise data
for state in states:
    f = (data[state]['districtData'])
    tc = []
    dis = []
    act, con, dea, rec = 0, 0, 0, 0
 
    # getting districtwise data
    for key in (data[state]['districtData']).items():
        district = key[0]
        dis.append(district)
        active = data[state]['districtData'][district]['active']
        confirmed = data[state]['districtData'][district]['confirmed']
        deaths = data[state]['districtData'][district]['deceased']
        recovered = data[state]['districtData'][district]['recovered']
        if district == 'Unknown':
            active, confirmed, deaths, recovered = 0, 0, 0, 0
        tc.append([active, confirmed, deaths, recovered])
        act = act + active
        con = con + confirmed
        dea = dea + deaths
        rec = rec + recovered
    tc.append([act, con, dea, rec])
    dis.append('Total')
    parameters = ['Active', 'Confirmed', 'Deaths', 'Recovered']

Creando DataFrame usando pandas

# creating a dataframe
df = pd.DataFrame(tc, dis, parameters)
print('COVID - 19', state, 'District Wise Data')
print(df)

Visualización de datos usando Matplotlib

# plotting of data
plt.bar(dis, df['Active'], width=0.5, align='center')
fig = plt.gcf()
fig.set_size_inches(18.5, 10.5)
plt.xticks(rotation=75)
plt.show()
print('*'*100)

Código de la función CasesData() final

# function to get data from api
def casesData():
    # getting the json data by calling api
    data = ((requests.get(url)).json())
    states = []
 
    # getting states
    for key in data.items():
        states.append(key[0])
 
    # getting statewise data
    for state in states:
        f = (data[state]['districtData'])
        tc = []
        dis = []
        act, con, dea, rec = 0, 0, 0, 0
 
        # getting districtwise data
        for key in (data[state]['districtData']).items():
            district = key[0]
            dis.append(district)
            active = data[state]['districtData'][district]['active']
            confirmed = data[state]['districtData'][district]['confirmed']
            deaths = data[state]['districtData'][district]['deceased']
            recovered = data[state]['districtData'][district]['recovered']
            if district == 'Unknown':
                active, confirmed, deaths, recovered = 0, 0, 0, 0
            tc.append([active, confirmed, deaths, recovered])
            act = act + active
            con = con + confirmed
            dea = dea + deaths
            rec = rec + recovered
        tc.append([act, con, dea, rec])
        dis.append('Total')
        parameters = ['Active', 'Confirmed', 'Deaths', 'Recovered']
 
        # creating a dataframe
        df = pd.DataFrame(tc, dis, parameters)
        print('COVID - 19', state, 'District Wise Data')
        print(df)
 
        # plotting of data
        plt.bar(dis, df['Active'], width=0.5, align='center')
        fig = plt.gcf()
        fig.set_size_inches(18.5, 10.5)
        plt.xticks(rotation = 75)
        plt.show()
        print('*' * 100)

Implementación definitiva:

# importing modules
import json
import requests
import pandas as pd
import matplotlib.pyplot as plt
 
# storing the url in the form of string
url = "https://api.covid19india.org/state_district_wise.json"
 
# function to get data from api
 
 
def casesData():
    # getting the json data by calling api
    data = ((requests.get(url)).json())
    states = []
 
    # getting states
    for key in data.items():
        states.append(key[0])
 
    # getting statewise data
    for state in states:
        f = (data[state]['districtData'])
        tc = []
        dis = []
        act, con, dea, rec = 0, 0, 0, 0
 
        # getting districtwise data
        for key in (data[state]['districtData']).items():
            district = key[0]
            dis.append(district)
            active    = data[state]['districtData'][district]['active']
            confirmed = data[state]['districtData'][district]['confirmed']
            deaths    = data[state]['districtData'][district]['deceased']
            recovered = data[state]['districtData'][district]['recovered']
            if district == 'Unknown':
                active, confirmed, deaths, recovered = 0, 0, 0, 0
            tc.append([active, confirmed, deaths, recovered])
            act = act + active
            con = con + confirmed
            dea = dea + deaths
            rec = rec + recovered
        tc.append([act, con, dea, rec])
        dis.append('Total')
        parameters = ['Active', 'Confirmed', 'Deaths', 'Recovered']
 
        # creating a dataframe
        df = pd.DataFrame(tc, dis, parameters)
        print('COVID - 19', state, 'District Wise Data')
        print(df)
 
        # plotting of data
        plt.bar(dis, df['Active'], width = 0.5, align = 'center')
        fig = plt.gcf()
        fig.set_size_inches(18.5, 10.5)
        plt.xticks(rotation = 75)
        plt.show()
        print('*' * 100)
 
 
# states data available through API
'''
0 State Unassigned
1 Andaman and Nicobar Islands
2 Andhra Pradesh
3 Arunachal Pradesh
4 Assam
5 Bihar
6 Chandigarh
7 Chhattisgarh
8 Delhi
9 Dadra and Nagar Haveli and Daman and Diu
10 Goa
11 Gujarat
12 Himachal Pradesh
13 Haryana
14 Jharkhand
15 Jammu and Kashmir
16 Karnataka
17 Kerala
18 Ladakh
19 Lakshadweep
20 Maharashtra
21 Meghalaya
22 Manipur
23 Madhya Pradesh
24 Mizoram
25 Nagaland
26 Odisha
27 Punjab
28 Puducherry
29 Rajasthan
30 Sikkim
31 Telangana
32 Tamil Nadu
33 Tripura
34 Uttar Pradesh
35 Uttarakhand
36 West Bengal
'''
 
#Driver Code
casesData()

Producción: