CORONAVIRUS DATA VISUALIZATION
In this data visualization, I will analyze Covid-19 data and will visualize it using Plotly and MATPLOTLIB in Python. This poster deals with creating bar charts and Choropeth graph.
This analysis summarizes the modeling, simulation, and analytics work around the COVID-19 outbreak around the world from the perspective of data science and visual analytics.
Tools and Technologies Used in the Project: Plotly and MATPLOTLIB in Google Colab(Runtime type – GPU) environment.
RACING BAR using MATPLOTLIB
The coronavirus disease COVID-19 was first reported in Wuhan, China, on December 31, 2019. The disease has since spread throughout the world, affecting 227.2 million individuals and resulting in 4,672,629 deaths as of September 9, 2021.
Static Choropleth Map of Covid-19
Total number of confirmed cases around the world on 25th April
Dynamic Choropleth Map of Covid-19
Countries being affected daily from January 2020- April 2020.
Top 10 Countries hit by most Covid19 cases by the end of April 2020
Using Bubble Chart
Top 10 Countries with the maximum Death Rate
Top 10 Countries with the maximum Recovery rate
