Data Products - Shiny Application Presentation

shiny app creation for the John Hopkins Data Science Specialization as part of the Coursera offerings

This peer assessed assignment has two parts. First, you will create a Shiny application and deploy it on Rstudio's servers. Second, you will use Slidify or Rstudio Presenter to prepare a reproducible pitch presentation about your application.

• Write a shiny application with associated supporting documentation. The documentation should be thought of as whatever a user will need to get started using your application.
• Deploy the application on Rstudio's shiny server
• Share the application link by pasting it into the provided text box
• Share your server.R and ui.R code on github

As a datascientists you work with lots of different data sets and the information can be foreign to you. One preprocessing step that you take is to make a histogram of each variable to get a understanding of the distribution of the data and if it is skewed or normally distributed. In sum cases it is a factor variable disguised as a numeric distribution. A example dataset into what it may look like below:

head(mtcars)

                   mpg cyl disp  hp drat    wt  qsec vs am gear carb
Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1

to make a histogram you type hist(mtcrs$mpg) and this works fine for small datasets but for larger datasets it becomes time consuming

To access the actual Shiny app please visit https://usmclee.shinyapps.io/Histogram/.

• Select desired variable from drop down menu
• Histogram automatically upates
• Repeat

Thanks for your time!