Stellenbosch University Student Enrolments Overview (Power BI) query evidence
ResourceKey: ce318c69-c98a-4884-9713-2c9927918524
Dataset modelId: 381132

Query 1: Distinct AcademicYear with total CountEnrolments (all data)
Decoded rows [AcademicYear, Sum(CountEnrolments)]:
  2021 -> 32255
  2022 -> 32535
  2023 -> 33656
  2024 -> 35370
  2025 -> 36219
Note: AcademicYear 2020 does not appear in the dataset (only 2021-2025 are present).

Query 2 filters applied:
  FirstTimeEntry = 'First Time Entry Student'
  SnapShot = 'June Stats'
  AcademicYear IN (2020, 2021, 2022)
  Faculty IN ('Engineering','Science','Law','Education')
Decoded rows [AcademicYear, Faculty, Gender, Sum(CountEnrolments)]:
  2021, Education, Female -> 192
  2021, Education, Male -> 29
  2021, Engineering, Female -> 208
  2021, Engineering, Male -> 503
  2021, Engineering, Non Binary -> 1
  2021, Law, Female -> 96
  2021, Law, Male -> 38
  2021, Law, Non Binary -> 1
  2021, Science, Female -> 463
  2021, Science, Male -> 321
  2021, Science, Non Binary -> 2
  2022, Education, Female -> 225
  2022, Education, Male -> 37
  2022, Education, Non Binary -> 2
  2022, Engineering, Female -> 246
  2022, Engineering, Male -> 503
  2022, Engineering, Non Binary -> 3
  2022, Law, Female -> 111
  2022, Law, Male -> 33
  2022, Science, Female -> 479
  2022, Science, Male -> 338
  2022, Science, Non Binary -> 2

Aggregated totals and female percentages (Female / Total * 100):
Year 2020:
  Engineering: no rows (N/A)
  Science: no rows (N/A)
  Law: no rows (N/A)
  Education: no rows (N/A)
Year 2021:
  Engineering: female=208, total=712, pct=29.213483146067% (rounded 29.21%) ; genders: Female=208, Male=503, Non Binary=1
  Science: female=463, total=786, pct=58.905852417303% (rounded 58.91%) ; genders: Female=463, Male=321, Non Binary=2
  Law: female=96, total=135, pct=71.111111111111% (rounded 71.11%) ; genders: Female=96, Male=38, Non Binary=1
  Education: female=192, total=221, pct=86.877828054299% (rounded 86.88%) ; genders: Female=192, Male=29
Year 2022:
  Engineering: female=246, total=752, pct=32.712765957447% (rounded 32.71%) ; genders: Female=246, Male=503, Non Binary=3
  Science: female=479, total=819, pct=58.485958485958% (rounded 58.49%) ; genders: Female=479, Male=338, Non Binary=2
  Law: female=111, total=144, pct=77.083333333333% (rounded 77.08%) ; genders: Female=111, Male=33
  Education: female=225, total=264, pct=85.227272727273% (rounded 85.23%) ; genders: Female=225, Male=37, Non Binary=2

Raw DSR (Query 2) ValueDicts:
{"D0": ["Education", "Engineering", "Law", "Science"], "D1": ["Female", "Male", "Non Binary"]}