Home

Intro to R

Part 1

Task: can you apply the functions sum and length to boolean vectors?

Yes - sum counts the number of TRUE values.

Task: make a list of booleans where the items are TRUE if each corresponding item of nums is less or equal to 3

nums <= 3

Task: make a list of booleans where the items are TRUE if each corresponding item of nums is either 5 or 1.

nums %in% c(5,1)

Task : Using y to index nums worked because the length of the two vectors are the same. What happens if you make another variable y2 which only has 3 boolean items, and try to index nums using that?

y2 = c(TRUE, FALSE, TRUE)
nums[y2]

Task: Find the favourite numbers of all my friends who have more than 4 characters in their name.

Hint: build this up step by step. First of all, get the number of characters in each name, then test whether this number is greater than 4. This should result in a vector of booleans. Then index nums using this vector.

nums[nchar(friends)>4]

Part 3

Task: What happens if you type d into the console to see what’s inside the object d?

You get a lot of data printed to the screen! Very unhelpful.

Task: Make a boolean vector which is TRUE if the latitude of a language is greater than 0, and FALSE otherwise. Assign this to a variable named `northernHemisphere’.

northernHemisphere <- d$latitude > 0

Task: Make a table of counts of basic word order types for languages in the northern hemisphere. Hint: you should index the rows with the variable northernHemisphere and the BasicWordOrder column.

table(d[northernHemisphere,]$BasicWordOrder)

Task: Load the data in data/Glottolog_Data.csv into a data frame called glottoData.

glottoData <- read.csv("../data/Glottolog_Data.csv", stringsAsFactors = F)

Task What are the names and formats of the variables in glottoData?

names(glottoData)

Task: Could you match the databases on the name of the language? Use d2 to find how many languages have different names in Glottolog versus WALS.

sum(d2$Name!=d2$glotto.name)

Part 4

Task: Which basic word order type has the higest mean latitude?

wordOrderLatitudeMEAN<- tapply(d2$latitude, d2$BasicWordOrder, mean)
wordOrderLatitudeMEAN.sorted <- sort(wordOrderLatitudeMEAN, decreasing = TRUE)
head(wordOrderLatitudeMEAN.sorted)

Part 5

Task: What happens if you try to calculate the sum of this variable?

You get NA returned!

Task: How many datapoints in ObjectVerbOrder are missing? How many glottocodes are missing? Remember that is.na creates a vector of booleans and sum can count the number of TRUE values in a vector.

sum(is.na(d$ObjectVerbOrder))
sum(is.na(d$glottocode))