stacking dataset using "for loop" function in R - r

Question

I'm having a trouble answering a homework question.
Create a larger dataset by stacking gm2
n=100 times over. That is, if nrg is the number
of rows of gm2 and ncg is the number of columns,
the larger dataset should have 100*nrg rows and
ncg columns.
Call your stacked dataset biggm2.
To create the stacked dataset,
initialize with biggm2 <- NULL and use
a for loop to build up biggm2 one layer
at a time. Time this code using the system.time() function.
An example use of system.time() to time an R
command, e.g., x <- rnorm(100000) is:
Code given:
system.time(
{
x <- rnorm(100000) # Could put multiple lines of R code here
})
I am new to R and this is taking too much time to find the answer. Hence, I'm asking this question here.
I'm using library(gapminder)
To add, 'gm2' is a dataset:
The columns year, lifeExp, pop and
gdpPercap and save this dataset as gm2.
Also coerce gm2 to a matrix and save as gm3.
This is what I did to read the dataset. Is this correct?
gm2 <- c(CanUS2$year, CanUS2$lifeExp, CanUS2$pop, CanUS2$gbpPercap)
gm2
gm3 <- matrix(gm2, nrow=24, ncol=4)
gm3
Or is this correct?
gm2 <- subset(CanUS2, select = c("year","lifeExp","pop","gdpPercap"))
But here, there is no point of coercing to a matrix since gm2 is already a matrix.
gm3 <- matrix(gm2v, nrow=24, ncol=4)
gm3
I am really confused.
Any advice will be really appreciated.

Answer 1

library(gapminder)
Tidyverse:
library(dplyr)
filter(gapminder, country %in% c("United States", "Canada")) %>%
select(year, lifeExp, pop, gdpPercap) -> tidyverse_can_us
head(tidyverse_can_us)
## # A tibble: 6 × 4
## year lifeExp pop gdpPercap
## <int> <dbl> <int> <dbl>
## 1 1952 68.75 14785584 11367.16
## 2 1957 69.96 17010154 12489.95
## 3 1962 71.30 18985849 13462.49
## 4 1967 72.13 20819767 16076.59
## 5 1972 72.88 22284500 18970.57
## 6 1977 74.21 23796400 22090.88
Base R:
gapminder[with(gapminder, country %in% c("United States", "Canada")),
c("year", "lifeExp", "pop", "gdpPercap")] -> base_r_can_us
head(base_r_can_us)
## # A tibble: 6 × 4
## year lifeExp pop gdpPercap
## <int> <dbl> <int> <dbl>
## 1 1952 68.75 14785584 11367.16
## 2 1957 69.96 17010154 12489.95
## 3 1962 71.30 18985849 13462.49
## 4 1967 72.13 20819767 16076.59
## 5 1972 72.88 22284500 18970.57
## 6 1977 74.21 23796400 22090.88
For either of those you've lost the factor variable that ties the values to the country. We also have no idea why you want/need a matrix. I made the assumption you were extracting Canada & U.S. data from your variable name but your entire question was mostly incoherent so it's hard to know what data you have and what outcome you want/need.