Upcharging older smokers
In this exercise, your objective is to examine how age and smoker status influence the cost of insurance premium charges. To achieve this, you will create a scatter plot that showcases insurance charges against age, grouped by smoker status. The DataFrame recipe will be employed to facilitate this process.
You can leverage the pre-loaded insurance
DataFrame, which contains the requisite data for the analysis. The DataFrames
and StatsPlots
packages have been imported.
This exercise is part of the course
Introduction to Data Visualization with Julia
Exercise instructions
- Utilize the recipe to create a scatter plot of the
insurance
DataFrame. - Plot the
:Charges
(y-axis) versus:Age
(x-axis) grouping by the:Smoker
column. - Customize the plot by setting the
markershape
to:rect
, themarkersize
to5
, and using marker colors:lightseagreen
and:crimson
.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Use recipe
____ ____ scatter(
# Pass columns
:____,
:____,
group=:____,
legend_title="Smoker",
# Customize markers
markershape=:____,
markersize=____,
markercolor=[:____ :____]
)
xlabel!("Age")
ylabel!("Insurance Premium (USD)")