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.
Diese Übung ist Teil des Kurses
Introduction to Data Visualization with Julia
Interaktive Übung
Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.
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)")