?? Uniting Forces: R and Python in Web Data Analysis ??

In my next blog, I address a common question with an innovative twist: Is R or Python better? But instead of choosing one, why not use both?

?? I explore how to run Python and R code within a single web scraping script, all from a single integrated development environment: RStudio. This integration not only optimizes the process but also expands our analytical tools.

?? I used Python to precisely extract and collecting data from a web page. Subsequently, with R, I generated detailed graphs to analyze this information. The synergy between the two languages enhances the capture and analysis of web data.

?? Within RStudio, through an RMarkdown script and the 'reticulate' library, I demonstrated how the interaction between Python and R can be facilitated. This requires the proper installation of the necessary libraries and modules for each language.

?? I invite you to discover how these two powerful languages can work together to provide deeper and more accurate insights into data analysis!

?? Setup Tips for Seamless Execution ??

Remember to install the necessary libraries and modules— I recommend doing this in the initial blocks (chunks) before running the script.

???? You can then proceed with the script available on the following GitHub link: github/miaacostach

?? Additionally, you can find the complete output in RMarkdown on Rpubs here: rpubs/miaacostach

?? Enjoy the code and unlock new potentials in your data analysis endeavors!