Python Exercise: Visualize Worldwide Confirmed Novel Coronavirus cases over time
Python Project: COVID-19 Exercise-14 with Solution
Write a Python program to visualize Worldwide Confirmed Novel Coronavirus (COVID-19) cases over time.
Sample Solution:
Python Code:
import pandas as pd
import plotly.express as px
import plotly.io as pio
pio.templates.default = "plotly_dark"
covid_data= pd.read_csv('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_daily_reports/03-19-2020.csv')
grouped = covid_data.groupby('Last Update')['Last Update', 'Confirmed', 'Deaths'].sum().reset_index()
fig = px.line(grouped, x="Last Update", y="Confirmed",
title="Worldwide Confirmed Novel Coronavirus(COVID-19) Cases Over Time")
fig.show()
Jupyter Notebook:
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What is the difficulty level of this exercise?
Python: Tips of the Day
F strings:
It is a common practice to add variables inside strings. F strings are by far the coolest way of doing it. To appreciate the f strings more, let's first perform the operation with the format function.
name = 'Owen' age = 25 print("{} is {} years old".format(name, age))
Output:
Owen is 25 years old
We specify the variables that go inside the curly braces by using the format function at the end. F strings allow for specifying the variables inside the string.
name = 'Owen' age = 25 print(f"{name} is {age} years old")
Output:
Owen is 25 years old
F strings are easier to follow and type. Moreover, they make the code more readable.
A, B, C = {2, 4, 6} print(A, B, C) A, B, C = ['p', 'q', 'r'] print(A, B, C)
Output:
2 4 6 p q r
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