Covid-19-Data-Analysis-Visualization

The first project of our data visualization studies is the COVID-19 data analysis project. In this project, we analyzed the data of the COVID-19 pandemic, which started in the first month of 2020 and still continues to affect the world, on the basis of countries. You can find the brief details of the project we realized in 3 stages in the readme file. We have tried to explain the details of the project step by step below. We wish you healthy days.

Covid-19-Data-Analysis-Visualization 1

First, we will download the libraries we will use.

!pip install folium -- !pip install plotly

import

import plotly.express as px
import plotly.graph_objects as go
import plotly.figure_factory as ff
from plotly.subplots import make_subplots

import folium

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

%matplotlib inline

import math 
import random
from datetime import timedelta

import warnings 
warnings.filterwarnings('ignore')

After importing our libraries, we defined our dataset.

!git clone https://github.com/laxmimerit/Covid-19-Preprocessed-Dataset

Total number of covid-19 cases in the world

Total number of covid-19 deaths in the world

Covid-19-Data-Analysis-Visualization 2

Confirmed Cases with Choropleth Map

Confirmed and Detah Cases with Static Colormap

Covid-19-Data-Analysis-Visualization 3

Line Plot

Growth Rate after 100k Cases

Tree Map Analysis

Deaths Cases

Covid-19 vs Other Similar Epidemics

We tried to show some important and striking graphics in our project above. You can find all the files of our first project in our data science journey in the github repo.