BMI versus age
In this exercise, your task is to manipulate the age and body mass index (BMI) data to generate a plot illustrating the average BMI progression among policyholders as they age. You will compare two approaches: one using the StatsPlots
plotting recipe for DataFrames and the other without it. Additionally, you will utilize chains to perform data manipulation and visualization.
The necessary packages, DataFrames
, StatsPlots
, Statistics
and Chain
, have already been imported for you, and the insurance
DataFrame is readily available.
This exercise is part of the course
Introduction to Data Visualization with Julia
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
grouped = groupby(insurance, :Age)
mean_bmis = combine(grouped, :BMI => mean)
# Scatter plot
scatter(____.____, ____.____,
label=false, smooth=____,
linewidth=3, linecolor=:maroon1)
xlabel!("Age")
ylabel!("Body Mass Index (BMI)")