Using .groupby() after reordering
It is now time to run some analyses on the adoptable dogs dataset that is focused on the "size" of the dog. You have already developed some code to reorder the categories. In this exercise, you will develop two similar .groupby() statements to help better understand the effect of "size" on other variables. dogs has been preloaded for you.
This exercise is part of the course
Working with Categorical Data in Python
Exercise instructions
- Print out the frequency table of
"sex"for each category of the"size"column. - Print out the frequency table of
"keep_in"for each category of the"size"column.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Previous code
dogs["size"].cat.reorder_categories(
new_categories=["small", "medium", "large"],
ordered=True,
inplace=True
)
# How many Male/Female dogs are available of each size?
print(dogs.____(____)[____].value_counts())
# Do larger dogs need more room to roam?
print(dogs.____(____)[____].value_counts())