Setup

R and RStudio

R is a free programming language for data analysis. RStudio is a free program that makes R easier to use. You need to install both, and R must be installed first.

For installation steps, see this R & RStudio lesson.

Install ggplot2

# Install & load ggplot2
install.packages("ggplot2")
library(ggplot2)

Prepare LFS Datasets

This guide uses two Labour Force Survey (LFS) datasets: Ontario 2025 and Ontario September 2026.

The code below collects the two datasets from Statistics Canada directly in R using the canpumf package and filters to Ontario using the dplyr package.

# Temporary storage
options(canpumf.cache_path = tempdir())   # LFS downloads
options(duckdb.home = tempdir())          # DuckDB helper files

# Install packages
install.packages(c("canpumf", "dplyr"))

# Load packages
library(canpumf)  # To pull LFS dataset
library(dplyr)    # To modify dataset

# Import datasets (before collecting)
get_pumf("LFS", "2025") |> close_pumf()
get_pumf("LFS", "2026-09") |> close_pumf()

# Collect 2025 Ontario
lfs25 <- get_pumf("LFS", "2025") |>
  filter(PROV == "Ontario") |>
  collect() |>
  rename_with(tolower)

# Collect September 2026 Ontario
lfs26sep <- get_pumf("LFS", "2026-09") |>
  filter(PROV == "Ontario") |>
  collect() |>
  rename_with(tolower)

LFS Variables Used

Variable names are uppercase in the original data. The code filters using PROV, then converts all names to lowercase, so the examples use lowercase variable names.

• PROV: Province
• survmnth: Survey month (1-12)
• lfsstat: Labour force status (employed, unemployed, or not in the labour force)
• gender: Gender (Men+, Women+)
• hrlyearn: Hourly wage (unit = cents)
• uhrsmain: Weekly hours (unit = tenths of an hour)
• finalwt: Final weight (number of people each respondent represents)

Technique: Extracting data
Tools: R
Data Format: Statistics