Learn practical skills, build real-world projects, and advance your career

COVID-19 Outbreak Analysis

Data Preprocessing

# All Imports Required Go Here

import requests
from datetime import datetime
from datetime import date
import os
import pandas as pd
import numpy as np
import plotly
import plotly.express as px
import plotly.graph_objects as go
from plotly.offline import init_notebook_mode
# Making sure that the plotly graphs and chloropleths can be seen
init_notebook_mode(connected=True)
# Data from the John Hopkins University Dataset on GitHub
# https://github.com/CSSEGISandData/COVID-19/tree/master/csse_covid_19_data/csse_covid_19_time_series

# Defining the variables required
filenames = ['time_series_covid19_confirmed_global.csv',
             'time_series_covid19_deaths_global.csv',
             'time_series_covid19_recovered_global.csv']

url = 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/'

# Making the main dataframes required for the analysis
confirmed_global = pd.read_csv(url + filenames[0])
deaths_global = pd.read_csv(url + filenames[1])
recovered_global = pd.read_csv(url + filenames[2])
country_cases = pd.read_csv('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/web-data/data/cases_country.csv')