This Shiny app explores
the Atlanta city employee salaries data for the Year 2015. In
particular, the relationship between employee salary
and variables
such as gender
, age
, and ethnic group
.
Dataset obtained from data.world, contributed by Brent Brewington.
- Selector Panel which allows user to select points using cursor (click-and-drag)
- Plot I displays the relationship of employee
median salary
byage
, seperated bygender
- Plot II displays the relationship of employee
median salary
byethnic group
, seperated bygender
- Table I which tabulates count at each combination of
ethnic group
andgender
This Shiny app is meant as a simple demonstration of how unbalanced dataset can be misleading at times. In statistics, this phenomenon is known as Simpson’s paradox or the Yule–Simpson effect.
If we look at male and female median salary
at various age group
, we
might observe that in general, male earns higher pay than female.
However, if we look at male and female median salary
by ethnic groups
, we notice that female’s median salary does not seem to lag
behind. As a matter of fact, both Asian and White women median salary
is actually higher than men by an obvious margin.
Tinker around the Shiny app to explore the data and understand the logic behind.
This Shiny app is shipped with Docker, built on rocker/tidyverse image.
# from this repo
git clone [email protected]:tmasjc/atl-salary-data.git
# move inside directory
cd atl-salary-data
# name your image
# it may take a while to build
docker build -t atl_salary_data .
# start your container
docker run -dp 3838:3838 atl_salary_data
## You are set. Go to localhost:3838/atl_salary_data to view application. ##
Or you can simply deploy it to Shiny server as per normal.