Read data into R.
classes <- read.csv("class.csv", stringsAsFactors = T)
Check the structure of the data frame.
str(classes)
## 'data.frame': 26 obs. of 40 variables:
## $ Timestamp : Factor w/ 26 levels "25/09/2017 08:59:41",..: 1 2 3 4 5 6 7 8 9 10 ...
## $ X1..Voting.in.general.elections.should.be.made.compulsory..like.in.Australia.. : Factor w/ 2 levels "I agree.","I disagree.": 1 1 1 1 1 1 1 1 1 2 ...
## $ X2..Maid.cafés.are.a.benefit.to.Japanese.culture. : Factor w/ 2 levels "I agree.","I disagree.": 1 1 1 1 1 1 1 2 1 2 ...
## $ X3..There.s.nothing.wrong.with.talking.on.a.mobile.phone.on.buses.or.trains. : Factor w/ 2 levels "I agree.","I disagree.": 2 2 2 2 2 2 2 2 2 2 ...
## $ X4..Japan.s.govt..should.not.force.teachers.to.sing.the.kimigayo.and.raise.the.hinomaru. : Factor w/ 2 levels "I agree.","I disagree.": 2 1 2 2 2 2 2 2 1 1 ...
## $ X5..In.Japan.today..most.people.don.t.need.English. : Factor w/ 1 level "I disagree.": 1 1 1 1 1 1 1 1 1 1 ...
## $ X6..Testing.on.animals..for.cosmetics...medicines.etc...should.be.banned. : Factor w/ 2 levels "I agree.","I disagree.": 1 2 1 1 2 1 2 2 1 1 ...
## $ X7..College.students.should.experience.living.by.themselves. : Factor w/ 2 levels "I agree.","I disagree.": 1 1 1 1 1 1 2 1 2 2 ...
## $ X8..Smoking.in.all.public.places.should.be.banned. : Factor w/ 2 levels "I agree.","I disagree.": 2 1 1 1 1 1 1 1 1 1 ...
## $ X9..The.hours.a.college.student.can.work.part.time.should.be.limited. : Factor w/ 2 levels "I agree.","I disagree.": 1 2 1 1 2 2 1 1 2 2 ...
## $ X10..School.uniforms.are.unnecessary. : Factor w/ 2 levels "I agree.","I disagree.": 2 2 1 2 2 2 2 1 1 2 ...
## $ X11..It.s.more.useful.to.learn.Chinese.than.English.as.a.second.language. : Factor w/ 2 levels "I agree.","I disagree.": 2 2 1 1 2 2 2 2 2 2 ...
## $ X12..People.in.Japan.who.drop.litter.should.be.fined. : Factor w/ 2 levels "I agree.","I disagree.": 1 2 2 1 1 2 2 1 2 1 ...
## $ X13..Japan.should.close.all.its.nuclear.power.plants. : Factor w/ 2 levels "I agree.","I disagree.": 1 1 1 1 2 2 1 1 1 1 ...
## $ X14..Japan.needs.to.develop.new.nuclear.power.plants.to.meet.the.demand.for.electricity. : Factor w/ 2 levels "I agree.","I disagree.": 2 2 1 2 1 2 1 1 2 1 ...
## $ X15..The.AO.and.recommendation.system.of.entering.university.should.be.abolished. : Factor w/ 2 levels "I agree.","I disagree.": 2 1 2 2 2 2 2 2 1 2 ...
## $ X16..PTAs.are.not.necessary.for.high.schools. : Factor w/ 2 levels "I agree.","I disagree.": 2 2 2 1 2 1 1 1 1 1 ...
## $ X17..It.s.more.interesting.to.watch.movies.made.from.novels.than.to.read.the.original.novels.: Factor w/ 2 levels "I agree.","I disagree.": 1 2 1 1 1 2 1 1 2 2 ...
## $ X18..The.age.that.Japanese.can.drink.alcohol.should.be.lowered.from.20.to.18.years.old. : Factor w/ 2 levels "I agree.","I disagree.": 2 2 1 1 2 2 1 1 1 2 ...
## $ X19..People.should.be.allowed.to.vote.at.the.age.of.18. : Factor w/ 2 levels "I agree.","I disagree.": 1 1 1 1 2 1 2 1 1 1 ...
## $ X20..Same.sex.marriage.should.be.allowed.everywhere. : Factor w/ 2 levels "I agree.","I disagree.": 1 1 1 1 2 1 1 1 1 1 ...
## $ X21..Co.educational.schools.are.better.than.women.only.schools.for.students. : Factor w/ 2 levels "I agree.","I disagree.": 2 2 1 1 1 1 1 1 2 1 ...
## $ X22..Every.college.and.university.should.have.a.sports.festival. : Factor w/ 2 levels "I agree.","I disagree.": 2 2 1 2 2 1 1 2 1 2 ...
## $ X23..High.school.education.should.be.compulsory. : Factor w/ 2 levels "I agree.","I disagree.": 1 1 1 1 1 1 1 1 1 1 ...
## $ X24..High.school.students.shouldn.t.bring.their.mobile.phones.to.school. : Factor w/ 2 levels "I agree.","I disagree.": 2 2 1 2 2 2 2 2 2 1 ...
## $ X25..The.age.that.Japanese.can.get.a.drivers.license.should.be.lowered.to.16. : Factor w/ 2 levels "I agree.","I disagree.": 2 2 2 2 2 2 2 1 2 2 ...
## $ X26..The.government.should.re.introduce.the.6.days.school.week. : Factor w/ 2 levels "I agree.","I disagree.": 2 2 2 2 1 2 2 2 2 2 ...
## $ X27..Using.a.paper.dictionary.is.better.than.an.electronic.dictionary. : Factor w/ 2 levels "I agree.","I disagree.": 2 2 1 2 2 1 2 2 1 2 ...
## $ X28..Learning.a.second.language.at.elementary.school.age.is.too.early. : Factor w/ 2 levels "I agree.","I disagree.": 2 2 2 2 1 2 2 2 2 2 ...
## $ X29..It.is.better.to.get.married.when.you.are.over.27. : Factor w/ 2 levels "I agree.","I disagree.": 2 1 1 2 1 1 1 2 1 2 ...
## $ X30..The.government.should.change.the.law.so.that.people.become.adult.at.18.years.old. : Factor w/ 2 levels "I agree.","I disagree.": 1 2 1 1 2 2 2 1 2 2 ...
## $ X31..Women.only.carriages.on.trains.should.be.in.operation.all.day. : Factor w/ 2 levels "I agree.","I disagree.": 1 1 1 2 2 1 2 2 1 2 ...
## $ X32..East.Asian.countries.should.have.a.common.currency.like.the.euro.in.Europe. : Factor w/ 2 levels "I agree.","I disagree.": 1 2 1 1 1 2 2 2 1 2 ...
## $ X33..Japan.should.change.article.9.and.have.a.normal.military. : Factor w/ 2 levels "I agree.","I disagree.": 1 2 2 2 2 2 2 1 1 2 ...
## $ X34..Japan.s.consumption.tax.should.be.increased.to.15.. : Factor w/ 2 levels "I agree.","I disagree.": 2 2 2 2 2 2 2 2 2 2 ...
## $ X35..Japan.should.be.stronger.in.its.relations.with.China. : Factor w/ 2 levels "I agree.","I disagree.": 1 2 1 1 1 2 2 1 1 2 ...
## $ X36..The.death.penalty.should.be.abolished. : Factor w/ 2 levels "I agree.","I disagree.": 2 2 2 1 2 2 2 2 1 2 ...
## $ X37..The.law.of.limitations.on.a.crime.should.be.abolished. : Factor w/ 2 levels "I agree.","I disagree.": 1 1 2 2 2 1 2 2 2 2 ...
## $ Name : Factor w/ 26 levels "Kana","Kaori",..: 18 12 23 7 20 4 2 21 1 14 ...
## $ Which.class.are.you.in. : Factor w/ 2 levels "Period 1 (8:50am to 10:20am)",..: 1 1 1 1 1 1 1 1 1 1 ...
Convert text strings “I agree.” to ones, and “I disagree.” to zeros.
classes <- as.data.frame(sapply(classes, function(x) gsub("I agree.", 1, x)))
classes <- as.data.frame(sapply(classes, function(x) gsub("I disagree.", 0, x)))
Convert character ones and zeros to numerics.
classes[,2:38] <- lapply(classes[,2:38], as.numeric)
Make students’ names the row names.
row.names(classes) <- classes$Name
Get rid of column variable for students’ names.
classes$Name <- NULL
Subset data for each class.
period_1 <- classes %>% filter(Which.class.are.you.in. == "Period 1 (8:50am to 10:20am)")
period_2 <- classes %>% filter(Which.class.are.you.in. == "Period 2 (10:30am to 12pm)")
Delete “Which class are you in?” variable.
period_1$Which.class.are.you.in. <- NULL
period_2$Which.class.are.you.in. <- NULL
Check the structure of one of these classes.
str(period_1)
## 'data.frame': 11 obs. of 38 variables:
## $ Timestamp : chr "25/09/2017 08:59:41" "25/09/2017 09:03:37" "25/09/2017 09:04:12" "25/09/2017 09:04:20" ...
## $ X1..Voting.in.general.elections.should.be.made.compulsory..like.in.Australia.. : num 1 1 1 1 1 1 1 1 1 0 ...
## $ X2..Maid.cafés.are.a.benefit.to.Japanese.culture. : num 1 1 1 1 1 1 1 0 1 0 ...
## $ X3..There.s.nothing.wrong.with.talking.on.a.mobile.phone.on.buses.or.trains. : num 0 0 0 0 0 0 0 0 0 0 ...
## $ X4..Japan.s.govt..should.not.force.teachers.to.sing.the.kimigayo.and.raise.the.hinomaru. : num 0 1 0 0 0 0 0 0 1 1 ...
## $ X5..In.Japan.today..most.people.don.t.need.English. : num 0 0 0 0 0 0 0 0 0 0 ...
## $ X6..Testing.on.animals..for.cosmetics...medicines.etc...should.be.banned. : num 1 0 1 1 0 1 0 0 1 1 ...
## $ X7..College.students.should.experience.living.by.themselves. : num 1 1 1 1 1 1 0 1 0 0 ...
## $ X8..Smoking.in.all.public.places.should.be.banned. : num 0 1 1 1 1 1 1 1 1 1 ...
## $ X9..The.hours.a.college.student.can.work.part.time.should.be.limited. : num 1 0 1 1 0 0 1 1 0 0 ...
## $ X10..School.uniforms.are.unnecessary. : num 0 0 1 0 0 0 0 1 1 0 ...
## $ X11..It.s.more.useful.to.learn.Chinese.than.English.as.a.second.language. : num 0 0 1 1 0 0 0 0 0 0 ...
## $ X12..People.in.Japan.who.drop.litter.should.be.fined. : num 1 0 0 1 1 0 0 1 0 1 ...
## $ X13..Japan.should.close.all.its.nuclear.power.plants. : num 1 1 1 1 0 0 1 1 1 1 ...
## $ X14..Japan.needs.to.develop.new.nuclear.power.plants.to.meet.the.demand.for.electricity. : num 0 0 1 0 1 0 1 1 0 1 ...
## $ X15..The.AO.and.recommendation.system.of.entering.university.should.be.abolished. : num 0 1 0 0 0 0 0 0 1 0 ...
## $ X16..PTAs.are.not.necessary.for.high.schools. : num 0 0 0 1 0 1 1 1 1 1 ...
## $ X17..It.s.more.interesting.to.watch.movies.made.from.novels.than.to.read.the.original.novels.: num 1 0 1 1 1 0 1 1 0 0 ...
## $ X18..The.age.that.Japanese.can.drink.alcohol.should.be.lowered.from.20.to.18.years.old. : num 0 0 1 1 0 0 1 1 1 0 ...
## $ X19..People.should.be.allowed.to.vote.at.the.age.of.18. : num 1 1 1 1 0 1 0 1 1 1 ...
## $ X20..Same.sex.marriage.should.be.allowed.everywhere. : num 1 1 1 1 0 1 1 1 1 1 ...
## $ X21..Co.educational.schools.are.better.than.women.only.schools.for.students. : num 0 0 1 1 1 1 1 1 0 1 ...
## $ X22..Every.college.and.university.should.have.a.sports.festival. : num 0 0 1 0 0 1 1 0 1 0 ...
## $ X23..High.school.education.should.be.compulsory. : num 1 1 1 1 1 1 1 1 1 1 ...
## $ X24..High.school.students.shouldn.t.bring.their.mobile.phones.to.school. : num 0 0 1 0 0 0 0 0 0 1 ...
## $ X25..The.age.that.Japanese.can.get.a.drivers.license.should.be.lowered.to.16. : num 0 0 0 0 0 0 0 1 0 0 ...
## $ X26..The.government.should.re.introduce.the.6.days.school.week. : num 0 0 0 0 1 0 0 0 0 0 ...
## $ X27..Using.a.paper.dictionary.is.better.than.an.electronic.dictionary. : num 0 0 1 0 0 1 0 0 1 0 ...
## $ X28..Learning.a.second.language.at.elementary.school.age.is.too.early. : num 0 0 0 0 1 0 0 0 0 0 ...
## $ X29..It.is.better.to.get.married.when.you.are.over.27. : num 0 1 1 0 1 1 1 0 1 0 ...
## $ X30..The.government.should.change.the.law.so.that.people.become.adult.at.18.years.old. : num 1 0 1 1 0 0 0 1 0 0 ...
## $ X31..Women.only.carriages.on.trains.should.be.in.operation.all.day. : num 1 1 1 0 0 1 0 0 1 0 ...
## $ X32..East.Asian.countries.should.have.a.common.currency.like.the.euro.in.Europe. : num 1 0 1 1 1 0 0 0 1 0 ...
## $ X33..Japan.should.change.article.9.and.have.a.normal.military. : num 1 0 0 0 0 0 0 1 1 0 ...
## $ X34..Japan.s.consumption.tax.should.be.increased.to.15.. : num 0 0 0 0 0 0 0 0 0 0 ...
## $ X35..Japan.should.be.stronger.in.its.relations.with.China. : num 1 0 1 1 1 0 0 1 1 0 ...
## $ X36..The.death.penalty.should.be.abolished. : num 0 0 0 1 0 0 0 0 1 0 ...
## $ X37..The.law.of.limitations.on.a.crime.should.be.abolished. : num 1 1 0 0 0 1 0 0 0 0 ...
Calculate the Euclidean distances between each student based on their answers to the social issues questionnaire. Then plot the dendrogram.
period_1 %>% dist %>% hclust %>% plot
## Warning in dist(.): NAs introduced by coercion
period_2 %>% dist %>% hclust %>% plot
## Warning in dist(.): NAs introduced by coercion
The students are now clustered according to their social values. In a previous lesson, they had delivered balanced presentations. Now they can be persuasive about an issue that concerns them.