U.S. News and World Report’s College Data#
Statistics for a large number of US Colleges from the 1995 issue of US News and World Report.
Private
: A factor with levels No and Yes indicating private or public universityApps
: Number of applications receivedAccept
: Number of applications acceptedEnroll
: Number of new students enrolledTop10perc
: Pct. new students from top 10% of H.S. classTop25perc
: Pct. new students from top 25% of H.S. classF.Undergrad
: Number of fulltime undergraduatesP.Undergrad
: Number of parttime undergraduatesOutstate
: Out-of-state tuitionRoom.Board
: Room and board costsBooks
: Estimated book costsPersonal
: Estimated personal spendingPhD
: Pct. of faculty with Ph.D.’sTerminal
: Pct. of faculty with terminal degreeS.F.Ratio
: Student/faculty ratioperc.alumni
: Pct. alumni who donateExpend
: Instructional expenditure per studentGrad.Rate
: Graduation rate
Source#
This dataset was taken from the StatLib library which is maintained at Carnegie Mellon University. The dataset was used in the ASA Statistical Graphics Section’s 1995 Data Analysis Exposition.
from ISLP import load_data
College = load_data('College')
College.columns
Index(['Private', 'Apps', 'Accept', 'Enroll', 'Top10perc', 'Top25perc',
'F.Undergrad', 'P.Undergrad', 'Outstate', 'Room.Board', 'Books',
'Personal', 'PhD', 'Terminal', 'S.F.Ratio', 'perc.alumni', 'Expend',
'Grad.Rate'],
dtype='object')
College.shape
(777, 18)
College.columns
Index(['Private', 'Apps', 'Accept', 'Enroll', 'Top10perc', 'Top25perc',
'F.Undergrad', 'P.Undergrad', 'Outstate', 'Room.Board', 'Books',
'Personal', 'PhD', 'Terminal', 'S.F.Ratio', 'perc.alumni', 'Expend',
'Grad.Rate'],
dtype='object')
College.describe().iloc[:,:4]
Apps | Accept | Enroll | Top10perc | |
---|---|---|---|---|
count | 777.000000 | 777.000000 | 777.000000 | 777.000000 |
mean | 3001.638353 | 2018.804376 | 779.972973 | 27.558559 |
std | 3870.201484 | 2451.113971 | 929.176190 | 17.640364 |
min | 81.000000 | 72.000000 | 35.000000 | 1.000000 |
25% | 776.000000 | 604.000000 | 242.000000 | 15.000000 |
50% | 1558.000000 | 1110.000000 | 434.000000 | 23.000000 |
75% | 3624.000000 | 2424.000000 | 902.000000 | 35.000000 |
max | 48094.000000 | 26330.000000 | 6392.000000 | 96.000000 |