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.
Diese Übung ist Teil des Kurses
Working with Categorical Data in Python
Anleitung zur Übung
- 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.
Interaktive Übung
Vervollständige den Beispielcode, um diese Übung erfolgreich abzuschließen.
# 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())