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 university

  • Apps: Number of applications received

  • Accept: Number of applications accepted

  • Enroll: Number of new students enrolled

  • Top10perc: Pct. new students from top 10% of H.S. class

  • Top25perc: Pct. new students from top 25% of H.S. class

  • F.Undergrad: Number of fulltime undergraduates

  • P.Undergrad: Number of parttime undergraduates

  • Outstate: Out-of-state tuition

  • Room.Board: Room and board costs

  • Books: Estimated book costs

  • Personal: Estimated personal spending

  • PhD: Pct. of faculty with Ph.D.’s

  • Terminal: Pct. of faculty with terminal degree

  • S.F.Ratio: Student/faculty ratio

  • perc.alumni: Pct. alumni who donate

  • Expend: Instructional expenditure per student

  • Grad.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