Manually collected daily snapshots of worldometer COVID-19 data (since April 18)

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F128750%2F66baee67b3e35bf9656ff816e692527e%2Fsnapshot_worldometer_july4.png?generation=1593988535797227&alt=media" alt="">

Content

The dataset contains data about the numbers of tests, cases, deaths, serious/critical cases, active cases and recovered cases in each country for every day since April 18, and also contains the population of each country to calculate per-capita penetration of the virus

I've removed data from the "Diamond Princess" and "MS Zaandam" since they are not countries

Additionally, an auxiliray table with information about the fraction of the general population at different age groups for every country is added (taken from Wikipedia). This is specifically relevant since COVID-19 death rate is very much age dependent.

Acknowledgements

The people at "www.worldometers.info" collecting and maintaining this site really are doing very important work "https://www.worldometers.info/coronavirus/#countries">https://www.worldometers.info/coronavirus/#countries

Data about age structure for every country comes from wikipedia

Inspiration

It's possible to use this dataset for various purposes and analyses My goal will be to use the additional data about the number of tests performed in each country to estimate the true death and infection rates of COVID-19

Analysis of ‘Population by Country - 2020’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/tanuprabhu/population-by-country-2020 on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

I always wanted to access a data set that was related to the world’s population (Country wise). But I could not find a properly documented data set. Rather, I just created one manually.

Content

Now I knew I wanted to create a dataset but I did not know how to do so. So, I started to search for the content (Population of countries) on the internet. Obviously, Wikipedia was my first search. But I don't know why the results were not acceptable. And also there were only I think 190 or more countries. So then I surfed the internet for quite some time until then I stumbled upon a great website. I think you probably have heard about this. The name of the website is Worldometer. This is exactly the website I was looking for. This website had more details than Wikipedia. Also, this website had more rows I mean more countries with their population.

Once I got the data, now my next hard task was to download it. Of course, I could not get the raw form of data. I did not mail them regarding the data. Now I learned a new skill which is very important for a data scientist. I read somewhere that to obtain the data from websites you need to use this technique. Any guesses, keep reading you will come to know in the next paragraph.

https://fiverr-res.cloudinary.com/images/t_main1,q_auto,f_auto/gigs/119580480/original/68088c5f588ec32a6b3a3a67ec0d1b5a8a70648d/do-web-scraping-and-data-mining-with-python.png" alt="alt text">

You are right its, Web Scraping. Now I learned this so that I could convert the data into a CSV format. Now I will give you the scraper code that I wrote and also I somehow found a way to directly convert the pandas data frame to a CSV(Comma-separated fo format) and store it on my computer. Now just go through my code and you will know what I'm talking about.

Below is the code that I used to scrape the code from the website

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F3200273%2Fe814c2739b99d221de328c72a0b2571e%2FCapture.PNG?generation=1581314967227445&alt=media" alt="">

Acknowledgements

Now I couldn't have got the data without Worldometer. So special thanks to the website. It is because of them I was able to get the data.

Inspiration

As far as I know, I don't have any questions to ask. You guys can let me know by finding your ways to use the data and let me know via kernel if you find something interesting

--- Original source retains full ownership of the source dataset ---

Worldometer çeşitli konular için sayaçlar ve gerçek zamanlı istatistikler sağlayan bir referans web sitesidir çevrimiçi

Introduction

The dataset contains COVID-19 statistics for the top countries currently affected by the virus. The data was scraped from two popular sites maintaining daily updates on the spread of COVID-19 - https://www.worldometers.info/ and https://en.wikipedia.org/wiki/COVID-19_pandemic

Contents

There are two kinds of csv files. One type of files are country wise daily statistics on COVID-19 spread. The data for the following countries is available:-

• United States
• Russia
• Brazil
• Pakistan
• Germany
• Peru
• Spain
• Belgium
• Italy
• Belarus
• India
• Qatar
• Mexico
• Turkey
• Sweden
• Saudi Arabia
• Iran
• Canada
• Chile
• China
• France
• Ecuador
• Bangladesh

For each of these countries, the dataset contains the following columns:-

• Date
• total cases
• daily cases
• active cases
• total deaths
• daily deaths

The second type of file is the overall statistics which contains statistics for all the countries affected in the world. This dataset contains the following columns:-

• country name
• total cases
• total recoveries
• total deaths