What Does COVID-19 and World Happiness Report Data Tell Us?

Photo by Matilda Wormwood from Pexels

For many people, the idea of ​​staying home actually sounded good at first. This process was really efficient for Netflix and Amazon. But then sad truths awaited us. What was boring was the number of dead and intubated patients one after the other. We all know the aftermath well.

In this article, we will try to examine the covid-19 virus, which can affect all countries in the world, and the relationship between it and the countries explained in the happiness report.

Before we start, let’s get to know our datasets:

• ‘covid19_Confirmed_dataset.csv’ (Data include 96 days from the first case)
• ‘worldwide_happiness_report.csv’

And of course the libraries we will use:

import pandas as pd 
import numpy as np 
import seaborn as sns
import matplotlib.pyplot as plt

First of all, we will need a small clearing of our data. We will follow the following procedures to obtain our data frame, where ‘Lat’ and ‘Long’ are removed from the columns:

corona_dataset_csv.drop(["Lat", "Long"],axis=1,inplace=True)

And only the country names and the number of cases are shown day by day:

corona_dataset_aggregated =…