In-class Exercise 1a: Now You 👀 It!

Loading R packages

In this hands-on exercise, 2 R packages will be used. They are:

• tidyverse

• haven

The code chunk used as follows:

pacman::p_load(tidyverse,haven)

Filtering PISA data

Note

the code under this section filtered PISA data to include only SG data

the dataset is saved as a rds file called stu_qqq_SG.rds and loaded back as a dataframe.

only stu_qqq_SG.rds will be imported for efficiency purpose for the rest of exercise.

The code chunk below uses read_sas() of haven to import PISA data into R environment.

stu_qqq <- read_sas("data/cy08msp_stu_qqq.sas7bdat")

The code chunk below use filter() of dplyr to filter observation in SG only.

stu_qqq_SG <- stu_qqq %>%
  filter(CNT == "SGP")

The code chunk below use write_rds() to save the data into rds format.

write_rds(stu_qqq_SG,
          "data/stu_qqq_SG.rds")

Importing filtered PISA data

The code chunk below uses read_rds() to import PISA SG data into R environment.

stu_qqq_SG <- read_rds("data/stu_qqq_SG.rds")