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canlang

R build status R build status

The goal of {canlang} is to easily share language data collected in the 2016 Canadian census. This data was retreived from the 2016 Canadian census data set using the {cancensus} R package.

This package contains three data sets:

  1. can_lang: Contains the counts of the total number of Canadians that report each language as their mother tongue, which language they speak most often at home, which language they use most often at work, and which language they have knowledge for.

  2. region_lang: For each census division, it contains the counts of how many Canadians report each language as their mother tongue, which language they speak most often at home, which language they use most often at work, and which language they have knowledge for.

  3. region_data: For each census division, it contains the statistics for number of households, land area, population and number of dwellings.

Installation

You can install the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("ttimbers/canlang")

Example usage of can_lang

The data set can_lang contains the counts of the total number of Canadians that report each language as their mother tongue, which language they speak most often at home, which language they use most often at work, and which language they have knowledge for. This data was recorded in the 2016 Census:

library(canlang)
head(can_lang)
#>                                  category                       language
#> 1                    Aboriginal languages   Aboriginal languages, n.o.s.
#> 2 Non-Official & Non-Aboriginal languages                      Afrikaans
#> 3 Non-Official & Non-Aboriginal languages Afro-Asiatic languages, n.i.e.
#> 4 Non-Official & Non-Aboriginal languages                     Akan (Twi)
#> 5 Non-Official & Non-Aboriginal languages                       Albanian
#> 6                    Aboriginal languages   Algonquian languages, n.i.e.
#>   mother_tongue most_at_home most_at_work lang_known
#> 1           590          235           30        665
#> 2         10260         4785           85      23415
#> 3          1150          445           10       2775
#> 4         13460         5985           25      22150
#> 5         26895        13135          345      31930
#> 6            45           10            0        120
library(ggplot2)
ggplot2::ggplot(data = can_lang,
       aes(x = most_at_home, y = mother_tongue, 
           colour = category, shape = category)) + 
    geom_point(alpha = 0.7) +
    scale_color_manual(values = c("blue3","red3","black")) +
    scale_y_log10(name = "Number of Canadians reporting the \n language as their mother tongue", 
                       labels = scales::comma) +
    scale_x_log10(name = "Number of Canadians speaking the language \n as their primary language at home", 
                       labels = scales::comma) +
    annotation_logticks() +
    theme_bw()

Example usage of region_lang

For each census metropolitan area (CMA), the data set region_lang contains the counts of how many Canadians report each language as their mother tongue, which language they speak most often at home, which language they use most often at work, and which language they have knowledge for.

library(canlang)
library(dplyr)
region_lang %>% 
    filter(region == "Vancouver") %>% 
    arrange(desc(mother_tongue)) %>% 
    head()
#> # A tibble: 6 x 7
#>   region  category  language  mother_tongue most_at_home most_at_work lang_known
#>   <chr>   <chr>     <chr>             <dbl>        <dbl>        <dbl>      <dbl>
#> 1 Vancou… Official… English         1316635      1622735      1330555    2289515
#> 2 Vancou… Non-Offi… Cantonese        184365       132185        22890     223700
#> 3 Vancou… Non-Offi… Mandarin         174920       138680        23195     250175
#> 4 Vancou… Non-Offi… Punjabi …        151205       104855        13125     187530
#> 5 Vancou… Non-Offi… Tagalog …         66825        30695          635      96290
#> 6 Vancou… Non-Offi… Korean            45990        34225         5075      50640

Example usage of region_data

For each census metropolitan area (CMA), the data set region_data contains the statistics for number of households, land area, population and number of dwellings.

library(canlang)
library(dplyr)
region_data %>% 
    arrange(desc(population)) %>% 
    head()
#> # A tibble: 6 x 5
#>   region            households  area population dwellings
#>   <chr>                  <dbl> <dbl>      <dbl>     <dbl>
#> 1 Toronto              2135909 6270.    5928040   2235145
#> 2 Montréal             1727310 4638.    4098927   1823281
#> 3 Vancouver             960894 3040.    2463431   1027613
#> 4 Calgary               519693 5242.    1392609    544870
#> 5 Ottawa - Gatineau     535499 7169.    1323783    571146
#> 6 Edmonton              502143 9858.    1321426    537634

Plain text, excel and SQLite database files

We have included several different plain text files, an excel files and a SQLite database file in this repo to be used for practice importing from these filetypes. Specifically, they are:

Canada-level

  • can_lang.csv: the same dataset available via canlang::can_lang stored as a vanilla .csv file.
  • can_lang-meta-data.csv: the same dataset available via canlang::can_lang stored as a vanilla .csv file with two rows of metadata that should be skipped.
  • can_lang.tsv: the same dataset available via canlang::can_lang stored as a .tsv (tab separated) file and has no column names.
  • can_lang.xlsx: the same dataset available via canlang::can_lang stored as a .xlsx file. Can be read in using the {readxl} package.
  • can_lang.db: the same dataset available via canlang::can_lang stored as a SQLite database (.db) file. Can be read in using the {RSQLite} package.

Census metroolitan area (CMA)-level

  • vancouver_lang.csv & calgary_lang.csv: data for Vancouver, BC and Calgary, AB, respectively, stored as a vanilla .csv file.
  • victoria_lang.csv: data for Victoria, BC stored as a vanilla .tsv file.
  • kelowna_lang.csv: data for Kelowna, BC stored as a .csv file (csv2 flavour) with metadata in the header and footer that should be skipped.
  • abbotsford_lang.xlsx: data for Abbotsford, BC stored as a .xlsx file where sheet 1 is the column names, and sheet 2 is the data with no column names. Can be read in using the {readxl} package.
  • edmonton_lang.xlsx: data for Edmonton, AB stored as a .xlsx file where all the data is in sheet 1.

How this was made

The data-raw directory contains the the scripts necessary to create everything in this package, including the R data objects and the plain text, excel and SQLite database files.

References

Data originally published in:

  • Source: Statistics Canada, Census of Population, 2016. Reproduced and distributed on an “as is” basis with the permission of Statistics Canada.

Package development resources:

  • von Bergmann, J., Aaron Jacobs, Dmitry Shkolnik (2020). cancensus: R package to access, retrieve, and work with Canadian Census data and geography. v0.3.2.