$-$ Use the demographic segmentation from the previous module to create a set of charts that will demonstrate $.$ the relationship between demographic segments and cost of claimHint: make sure to apply appropriate summary statistics to your charts in order to account for any uneven groups breakdown $($for example, retired status$)$

Data Structurestr$($Insurance$\_$data$)$

# Create visualizations for demographic segmentation

# MariGE Distributionggplot$($Insurance$\_$data, aes$($x $=$ marital$))+$geom$\_$histogram$($binwidth $=5,$ fill $=$ "orange", color $=$ "black"$)+$labstitle $=$ "Marital Distribution of Customers"

#Gender Distributionggplot$($Insurance$\_$data, aes$($x $=$ gender, fill $-$ gender$))+$geom$\_$bar$)+$ scale$\_$fill$\_$manual $($values $=$ c$("0"=$ "blue"$1"=$pink"$))$Labs$($title $=$ "Gender Distribution of Customers", x $=$"Gender", y $=$ "Count"$)+$

# Townsize Distributionggplot$($Insurance$\_$data, aes$($x $=$ townsize, fill $=$ townsize$))+$geom$\_$bar$)+$labs$($title $=$ "Townsize Distribution of Customers", x $=$ "Townsize", y $=$ "Count"$)$