1. The document discusses visualizing analytical data on the web using R and RStudio. It outlines the steps to install RStudio, prepare data for visualization from a .xlsx file, create bar charts in RStudio showing internet prices by region, and publish the charts online using RPubs. 2. Key steps include loading the readxl library to import excel data, using barplot commands to generate charts specifying variables for prices and regions, and publishing charts to RPubs by selecting from the publish menu. 3. The example chart shows internet prices are highest in the Sahara desert region.

1. Visualize analytical data on the web
Artur Machura
07.01.2023, Katowice

2. Abstract
▪ Opening the presentation
▪ Introduction
▪ Main part
▪ Conclusion

3. Milestones (in my case study)
1. Install IDE (Integrated Development
Environment)
2. Prepare data for visualization (my case
is about the average internet price in
different regions of the world)
3. Create a chart
4. Publish a chart

4. Understand the basics concepts
1. R Language
(https://en.wikipedia.org/wiki/R_(progra
mming_language)
2. RStudio (RStudio is now Posit
https://posit.co/ )
3. RPubs (https://rpubs.com/ )

5. Install IDE
1. Install R package for you operating
system (RStudio requires R 3.3.0+)
▪ https://cran.rstudio.com/
2. Install RStudio Desktop (alternatively,
the server version, if you need one)
▪ https://posit.co/download/rstudio-
desktop/

6. Prepare data for visualization
(slide 1/2)
1. Open the RStudio console (alternatively use window
functions)
2. Load the readxl library ( this is the library needed to
import load .xlsx file, by the way – I’ll be using a file
downloaded from kaggle.com )
library(readxl)
3. Load the file (I use the console, but there is also an
option in the menu)

7. Prepare data for visualization
(slide 2/2)
4. The result is an object with two variables (these names will be
of importance in further work)

8. Create a chart in RStudio (slide
1/3)
1. Decide what kind of chart you need (depending on
this decision you will use different commands in the
console, this decision may also affect the library you’ll
use, more https://r-graph-gallery.com/all-graphs.html )
2. In my case I generate bar chart (very popular)
barplot(data$price,names.arg=(data$region))
Command name (object name$variables,argument=(object name$label for bar))

9. Create a chart in RStudio (slide
2/3)
3. You can additionally use some options for Your
graph (for example - I need to place bar names
vertically, because these horizontal names are
illegible, more
https://www.rdocumentation.org/packages/graphics/v
ersions/3.6.2/topics/barplot )
barplot(data$price,names.arg=(data$region),las=2,col=rainbow(10))
(additionally arguments is las and col)

10. Create a chart in Rstudio (slide
3/3)
By the way, the most
expensive internet is in
the Sahara desert

11. Publish a chart (step 1/2)
1. Choose an option
from the menu
Publish>Publish
Plot>Pblish to
RPubs>

12. Publish a chart (step 2/2)
2. Complete the
description in the
html generator (Title,
Description) and click
„Continue”
3. Your chart is now
available on the
Internet, and that
was the purpose of
this work!

13. Source
▪ https://posit.co/
▪ https://posit.co/download/rstudio-desktop/
▪ https://cran.rstudio.com/
▪ and others mentioned in the presentation

14. Thank you for your
attention! Please submit
any comments on the
software-engineers.org
PhD Artur Machura
arturmachura.info