R you ready to witness COVID-19? | Plotly & Tableau Visualizations
Updated as of May 20,2020
For the past few months, the news and social media from local to international have been broadcasting one thing, COVID-19. The sudden escalation of virus that formed chains bigger than the block-chain and networked faster than neural networks and emerged as a global epidemic. Along with the general news, the one common thing everyone might have seen is the data visualization of COVID-19 showing its impact.
Data have played a crucial roles in assessing and controlling Corona virus. Starting from tracking the affected people to calculating the deceased and recovery rate, data visualizations have been a guide for the health workers. It is definite that there are many websites which displays better dashboards of covid-19 spread plots, I decided to contribute to the galaxy of analysis in coronavirus spread and learn while working on this project.
We are going to see the notebook is written over R markdown script and have plotted all the graphs using ‘plotly’ package. Later we will see the Tableau dashboard at the end.I’m not going to bore you with the technical part as it has been already taken care of. Now let’s dive into analytics of COVID-19
Before going into the plots, the below displayed graphs are interactive, the readers can interact to the graphs and see in a much better view in my Kaggle report: Plotly Visualizations of COVID 19 in World & India. Please do visit and interact with the plots
1. Top 15 -Bar chart
World Nation
The following graph shows which countries tops as per the data , We can clearly see the distribution of top 15 world nation affected by the virus. If you want to interact with the plot please visit my kaggle notebook
Let’s talk about the country with high concern-USA, as you can see the number of cases in United States have dramatically increased.I found this interesting answer in Quora on why cases got escalated in US which I would like to quote here-
I think it’s because a large percentage of our population are not taking it seriously.What people are not taking into consideration is how contagious this virus is. It is considered 3–10 times more contagious than the seasonal flu. According to the CDC, 8.3% of the United States have contracted the seasonal flu this year, and although exact figures are not possible with the lack of sufficient testing kits, COVID-19 is expected to infect a minimum of 20% of our population, with one predictive model out of London indicating that might go as high as 81% of Americans. Based on our population of 327 million, that’s a range of 65 million to 242 million cases. Too many people aren’t following common sense suggestions and state and federal directives to remain at home even if they are not showing any symptoms of infection. They may not have symptoms, but ignoring guidelines to stay at home and practice social distancing can possibly result in passing it on to an elderly person, someone of their parents’ ages or grandparent’s ages for whom it may become serious and even fatal.
Indian states
The following graph shows which Indian State tops as per the data , We can clearly see the distribution of top 15 states affected by the virus. If you want to interact with the plot please visit my kaggle notebook
If you see the top states in the plot, we can infer that these states have high population industry and these are the most happening states with more industries and business hubs. News reports say that these states weren’t properly prepared with hospital facilities and many of the people didn’t follow lockdown which led to the rise in number of cases.
2. Death, Recovery and Active status- Bar chart
World Nation(Sample: 30)
The following graph shows which the death,recovered and active for a sample of 30 countries.We can clearly see active cases are higher and death cases are lower. If you want to interact with the plot please visit my kaggle notebook as this blog doesn’t support plotly feature. You can also change the sample count using my code available in my kaggle notebook
Indian States(Sample: 10)
The following graph shows which the death,recovered and active for a sample of 10 states.We can clearly see active cases are higher and death cases are lower. If you want to interact with the plot please visit my kaggle notebook as this blog doesn’t support plotly feature. You can also change the sample count using my code available in my kaggle notebook
I have a question, If the coronavirus has a 95% recovery rate, then what’s with all the hype? and here’s an answer from Stephen Taylor
Because most of the world could easily end up looking like Venezuela by this time next year. Bear with me.Death rate from the virus itself is just the tip of the iceberg. The global ripple effect from the measures taken to prevent it — or to ignore it — could be the most horrifying thing you’re ever going to see in your life.
3. Time series analysis
Trend line of World
The below trend chart shows how the active, death and recovered cases have been increased in World Nations, as you see the increasing rate of virus spread is rapid. The escalation starts in the mid of March.
Trend line of India
The below trend chart shows how the active, death and recovered cases have been increased in India, as you see the increasing rate of virus spread is rapid. The escalation starts in the mid of April.
4. India Vs Rest of the World-Line Chart
The following is a comparative line chart showing the cases in India and rest of the World nations. You can see where India stands!
I have a question, Is India comparatively less affected by the Corona virus scare? and here’s an answer from Vaishnavi Chavan
I have read quite a lot and have done some research about COVID-19. India having the second largest population has fewer cases as compared to other countries. I somehow thought if it reaches India, there wouldn’t be any way to curb it. This is because India less advance technology and high population which would cause it to spread faster.India was fast enough to ban visa on arrival and several flights to high risk countries were cancelled. Passengers were screened at the airports with high density. Partial lockdowns are also observed in several states.Also, Food that Indians consume is cooked for a long time. Almost every Indian dish is cooked for 30–45 minutes which kills the virus. Any kind of meat is usually cooked a lot in order to make it tender and most Indians prefer eating curries instead of salads. These could be the reasons
5. Recovery Vs Death rate-Bubble Chart
World Nations
The following is a bubble chart which shows the recovery and date rate of World Nations, do interact with the graphs to see the details in tooltip . Visit my kaggle notebook to interact with each bubble
Indian States
The following is a bubble chart which shows the recovery and date rate of Indian states, do interact with the graphs to see the details in in tooltip . Visit my kaggle notebook to interact with each bubble
Tableau Public Dashboards
Now, It’s time for us to jump into the King of visualization tool, Tableau. Presenting you the Dashboards, Please visit my tableau public profile to interact with the dashboard
World Nations- Tableau Dashboard
Indian States- Tableau Dashboard
That’s all folks ! If you want to check out few interacted pictures, find it in the appendix. It might sound cliché. But this plots can be visualized at a better way here. Click this-kaggle notebook . If you find this article worthwhile, Kindly share it with your friends.
Appendix for Kaggle Notebook
These pictures are captured when interacted. Please visit my Kaggle Notebook for interacting with the plots and gain maximum insights
Reference: Plotly Python Tutorial for Machine Learning Specialists
