Predictive Hacks

Web Scraping worldometers for Coronavirus

One of the most popular web pages about Covid-19 is the worldometers which provides a detailed report about Coronavirus cases by country. Today, we will show how we can use R to Web Scrape the summary table of the site.


url <- ""


# There are some "+" symbols and the "," 
# for the thousand separators that we wan to remove them
my_table[]<-lapply(my_table, function(x) (gsub("\\,|\\+", "", (x))))

# convert all but the first and last column to numeric

my_table[,c(3:12)] <- sapply(my_table[c(3:12)],as.numeric)

Since we got the data and we cleaned them, we can provide some statistics like:

Q: Which are the top 10 countries in Deaths per 1M Population?

my_table%>%arrange(-`Deaths/1M pop`)%>%
          select(`Country,Other`,`Deaths/1M pop`)%>%
   Country,Other Deaths/1M pop
1     San Marino          1032
2        Andorra           375
3          Spain           363
4          Italy           322
5        Belgium           311
6         France           212
7   Sint Maarten           210
8    Netherlands           160
9             UK           156
10   Switzerland           126

Enjoy your analysis!

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8 thoughts on “Web Scraping worldometers for Coronavirus”

  1. please guide me about this Warning messages:
    1: In lapply(X = X, FUN = FUN, …) : NAs introduced by coercion
    2: In lapply(X = X, FUN = FUN, …) : NAs introduced by coercion
    3: In lapply(X = X, FUN = FUN, …) : NAs introduced by coercion
    4: In lapply(X = X, FUN = FUN, …) : NAs introduced by coercion

    • This means that some values like NA and N/A etc are converted to NAs. They also changed the format of the table. I fixed it now.


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