RMHI PSYC30013 Codes RMHI Data Manipulation and Visualization Techniques Guide fall 2026 University of Melbourne

RMHI PSYC30013 Codes RMHI Data Manipulation and
Visualization Techniques Guide fall 2026 University of
Melbourne




RMHI CODES




LOADING DATA

library(here)
loc <- here(“bunnysurvey.csv”)



Loc<- here("gladlysurvey.cvs")

Gdata <- read_cvs(file=loc)



MAKING VARIABLES

Variable <-c(content, content, content)



VIEWING DATA

Data$height

Data$age

,MANIPULATING DATA

Data$height + 45

If you want to update this variable

D$height <- D$height +45

REMOVING DATA
data$tall <- NULL

CHANGING THE DATA IN THE TABLE
data$height[1] <- 99
data

REMOVING DATA

Data$tall <-NULL

,FILTERING DATA

Filter( gdata$age > 5)



OR



d%>%

Filter( age > 5)



SELECTING ELEMENTS FROM A TIBBLE

1. Data$height[1]
2. Data[ROW, COLUMN]
3. Data[1,”Height”]




SELECTING A WHOLE ROW

1. d[1, ] = row 1, all columns

2. d[, 1] = all rows, column 1

3. d[1:3, ] = rows 1 to 3, all columns



SELECTING ROWS AND COLUMNS

Data(c(1,2,4),c(“name”,”colour”)



Rows 1-4 and columns 1-3

, Data[1:4,1:3]



SELECTING ROWS THAT MATCH THE CRITERION

SmallOnes <- data$height<20

Data[SmallOnes,]



IF DATA IS MISSING
gdata$age[20] <- NA
# calculate the mean of the new vector
mean(gdata$age,na.rm=TRUE)



CALCULATING MEDIAN

median(gdata$age)

[1] 5
quantile(gdata$age,0.5)
50%
[1] 5



CALCULATING THE MODE

> modeOf(gdata$age)
[1] 3 5 4
> maxFreq(gdata$age)
[1] 6




RMARKDOWN