I am building a machine learning model for a binary classification task in Python/ Jupyter Notebook. I am currently in the "Exploratory data analysis" phase and try to create multiple plots/ graphs for my data set.
My data set consists of 20 columns (19 features and 1 labeled target). Each row in my data set represents a person. There are many categorical/ nominal features in my data set and only few numerical/ continuous ones. Unfortunately I cannot upload the real data set, so I will create a dummy one.
My aim is to create a plot/ graph to visualize the relationship between the binary variable
TARGET_happiness (meaning "is the person happy?") and the categorical variable
car (meaning "which car does this person own").
The plot I've used for binary
TARGET_happiness vs. continuous
age is a box plot, see:
This seems fine. Now I also try to use a box plot for binary
TARGET_happiness vs. categorical
I'm not sure if this plot is useful / appropriate. Sure, you can see that Tesla owners seem to be happier than BMW owners. But the box for Ford owners looks strange.
Which type of plot/ graph can I use to better visualize the relationship between binary and categorical data?