December 2018
Beginner to intermediate
682 pages
18h 1m
English
We might want to explore more and answer the question: For the schools with more black students than any other race, what is the distribution of its second highest race percentage?
>>> college_black = college_ugds[highest_percentage_race == 'UGDS_BLACK']>>> college_black = college_black.drop('UGDS_BLACK', axis='columns')>>> college_black.idxmax(axis='columns').value_counts(normalize=True)UGDS_WHITE 0.661228
UGDS_HISP 0.230326
UGDS_UNKN 0.071977
UGDS_NRA 0.018234
UGDS_ASIAN 0.009597
UGDS_2MOR 0.006718
UGDS_AIAN 0.000960
UGDS_NHPI 0.000960
dtype: float64
We needed to drop the UGDS_BLACK column before applying the same method from this recipe. Interestingly, it seems that these schools with higher black populations have a tendency ...