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Covid-19 Spread Analysis using Python

Covid-19 Spread Analysis using Python

In this blog , we will project the total number of confirmed cases of COVID-19 for a country .

First of all , Import required libraries

In [1]:

import pandas as pd
import matplotlib.pyplot as plt
import plotly.express as px
import numpy as np
import plotly
import plotly.graph_objects as go
from plotly.subplots import make_subplots

In [5]:

import requests
# Getting Data
url_request = requests.get("covid-data.json")
url_json = url_request.json()
df = pd.DataFrame(url_json['features'])

In [3]:

import datetime as dt

# a. transforming data

data_list = df['attributes'].tolist()
data = pd.DataFrame(data_list)
data.set_index('OBJECTID')
data = data[['Province_State','Country_Region','Last_Update','Lat','Long_','Confirmed','Recovered','Deaths','Active']]
data.columns = ('State','Country','Last Update','Lat','Long','Confirmed','Recovered','Deaths','Active')
data['State'].fillna(value = '', inplace = True)
data

# b. cleaning data

def convert_time(t):
    t = int(t)
    return dt.datetime.fromtimestamp(t)

data = data.dropna(subset = ['Last Update'])
data['Last Update'] = data['Last Update']/1000
data['Last Update'] = data['Last Update'].apply(convert_time)
data

Out[3]:

	State	Country	Last Update	Lat	Long	Confirmed	Recovered	Deaths	Active
0		Afghanistan	2021-04-20 14:50:41	33.939110	67.709953	57898	52272	2546	3080
1		Albania	2021-04-20 14:50:41	41.153300	20.168300	129694	102171	2347	25176
2		Algeria	2021-04-20 14:50:41	28.033900	1.659600	119805	83514	3160	33131
3		Andorra	2021-04-20 14:50:41	42.506300	1.521800	12805	12203	123	479
4		Angola	2021-04-20 14:50:41	-11.202700	17.873900	24518	22600	563	1355
...	...	...	...	...	...	...	...	...	...
761	Ohio	US	2021-04-20 14:50:41	40.388783	-82.764915	1054807	0	18991	0
762	Alabama	US	2021-04-20 14:50:41	32.318200	-86.902300	522512	0	10790	0
763	North Carolina	US	2021-04-20 14:50:41	35.630066	-79.806419	949366	0	12418	0
764	District of Columbia	US	2021-04-20 14:50:41	38.897438	-77.026817	46740	0	1096	0
765	Maine	US	2021-04-20 14:50:41	44.693947	-69.381927	57545	0	767	0

764 rows × 9 columns

In [4]:

# a. Top 10 confirmed countries (Bubble plot)

top10_confirmed = pd.DataFrame(data.groupby('Country')['Confirmed'].sum().nlargest(10).sort_values(ascending = False))
fig1 = px.scatter(top10_confirmed, x = top10_confirmed.index, y = 'Confirmed', size = 'Confirmed', size_max = 120,
                color = top10_confirmed.index, title = 'Top 10 Confirmed Cases Countries')
fig1.show()