Warmup
Next, complete the following warmup exercises as a team.
How many unique subject codes?
// TODO: replace with code that computes the actual result
var subjectCodes = _.pluck(data, 'Subject')
var result = _.uniq(subjectCodes)
return _.size(result)
They are 113 unique subject codes.
How many computer science (CSCI) courses?
// TODO: replace with code that computes the actual result
var subjectCodes = _.pluck(data, 'Subject')
var result = _.filter(subjectCodes, function(a){
return a == "CSCI"
})
return _.size(result)
They are 63 computer science courses.
What is the distribution of the courses across subject codes?
// TODO: replace with code that computes the actual result
var list = _.groupBy(data, function(college){
return college['Subject']
})
return _.mapValues(list, function(courses){
return courses.length
})
HIST |
78 |
HONR |
20 |
HUMN |
17 |
IAFS |
20 |
IPHY |
134 |
LING |
33 |
MATH |
232 |
MCDB |
117 |
BAKR |
3 |
PHIL |
160 |
PHYS |
76 |
PSCI |
117 |
NRSC |
17 |
PSYC |
123 |
WRTG |
402 |
RLST |
24 |
SLHS |
70 |
SOCY |
136 |
ARAB |
10 |
PORT |
7 |
SPAN |
162 |
COMR |
12 |
FARR |
20 |
GSAP |
3 |
INVS |
11 |
PACS |
4 |
SEWL |
8 |
DNCE |
62 |
THTR |
66 |
WMST |
29 |
ACCT |
45 |
BADM |
31 |
BCOR |
53 |
BSLW |
3 |
BUSM |
3 |
CESR |
7 |
ESBM |
24 |
FNCE |
44 |
INBU |
7 |
MBAC |
20 |
MBAX |
34 |
MGMT |
57 |
MKTG |
37 |
REAL |
12 |
EDUC |
139 |
ASEN |
48 |
CHEN |
49 |
CSCI |
63 |
AREN |
23 |
CVEN |
77 |
ECEN |
67 |
EMEN |
23 |
EHON |
5 |
GEEN |
65 |
EVEN |
2 |
HUEN |
37 |
MCEN |
90 |
TLEN |
24 |
ATLS |
44 |
MUSM |
5 |
RSEI |
2 |
JOUR |
96 |
LAWS |
176 |
CONV |
2 |
EMUS |
42 |
MUEL |
44 |
MUSC |
95 |
PMUS |
56 |
TMUS |
2 |
AIRR |
12 |
MILR |
9 |
NAVR |
9 |
CSVC |
1 |
LDSP |
14 |
NRLN |
1 |
PRLC |
3 |
ARCH |
1 |
ENVD |
59 |
ARTH |
13 |
ARTS |
52 |
CAMW |
2 |
CWCV |
1 |
LGBT |
1 |
LIBB |
6 |
CHIN |
10 |
FRSI |
1 |
HIND |
1 |
JPNS |
16 |
KREN |
3 |
ANTH |
53 |
APPM |
52 |
ASTR |
23 |
ARSC |
24 |
ATOC |
25 |
CHEM |
139 |
CLAS |
27 |
COMM |
78 |
EBIO |
113 |
ECON |
61 |
ENGL |
125 |
ENVS |
20 |
ETHN |
22 |
FILM |
33 |
FREN |
30 |
ITAL |
16 |
GEOG |
28 |
GEOL |
37 |
GRMN |
26 |
HEBR |
5 |
RUSS |
16 |
SCAN |
4 |
SWED |
1 |
LEAD |
1 |
What subset of these subject codes have more than 100 courses?
// TODO: replace with code that computes the actual result
var list = _.groupBy(data, function(college){
return college['Subject']
})
var values = _.mapValues(list, function(courses){
return courses.length
})
var result = _.pick(values, function(a){
return a > 100
})
return result
IPHY |
134 |
MATH |
232 |
MCDB |
117 |
PHIL |
160 |
PSCI |
117 |
PSYC |
123 |
WRTG |
402 |
SOCY |
136 |
SPAN |
162 |
EDUC |
139 |
LAWS |
176 |
CHEM |
139 |
EBIO |
113 |
ENGL |
125 |
What subset of these subject codes have more than 5000 total enrollments?
// TODO: replace with code that computes the actual result
var groups = _.groupBy(data, function(college){
return college['Subject']
})
var courseEnroll = _.mapValues(groups, function(a){
return _.map(a, function(b){
return b['N']['ENROLL']
})
})
var enroll = _.mapValues(courseEnroll, function(enrolls){
return _.sum(enrolls)
})
return _.pick(enroll, function(number){
return number > 5000
})
IPHY |
5507 |
MATH |
8725 |
PHIL |
5672 |
PHYS |
8099 |
PSCI |
5491 |
PSYC |
8477 |
WRTG |
7185 |
SOCY |
7932 |
BCOR |
6852 |
LAWS |
5166 |
What are the course numbers of the courses Tom (PEI HSIU) Yeh taught?
// TODO: replace with code that computes the actual result
var courses= _.filter(data, function(course){
var instructor= _.filter(course['Instructors'], function(instructor){
return instructor['name'] == 'YEH, PEI HSIU'
})
return _.size(instructor) > 0
})
return _.map(courses, function(course){
return course['Course']
})