In tweed1e/canmap: Standard Canadian geography shapefiles

knitr::opts_chunk$set(
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canmap

canmap provides easy access to standard Canadian geographic shapefiles, as well as the associated metadata that helps pick which one you'd like. It's named after mapbox, but instead of a box it's a can. Except mapcan was already taken on CRAN.

Installation

You can install the external development version of canmap with:

remotes::install_github("tweed1e/canmap")

And you can install the internal development version of canmap with:

remotes::install_gitlab("tweejes/canmap", host = "gitlab.statcan.ca")

Example

library(canmap)

default_shp <- dplyr::filter(shapefile_paths,
                  geo_code == "pr_" &
                  file_type == "digital boundary file" &
                  format == "ArcGIS (.shp)" &
                  language == "english"  &
                  ref_date == 2016 &
                  projection == "projection in Lambert conformal conic"
                )

default_shp

# then pick a shapefile and get the link:
(url <- default_shp[1, ]$path)

# then you can download it yourself, or use download_geography(url)
shp_path <- download_geography(url)

# and use sf to read the shapefile.
provinces <- sf::read_sf(shp_path)

Then input into ggplot + sf:

``` {r fig.retina = 2} library(ggplot2)

ggplot() + geom_sf(data = provinces) + theme_minimal() + labs(title = "Provinces & Territories / Digital Boundary File", x = "Longitude", y = "Latitude", caption = paste0(".zip source name: ", default_shp$filepath, ".zip"))

## Documentation 


A list of useful links to clean up later:

* [Geography definitions and documentation](https://www.statcan.gc.ca/eng/subjects/standard/sgc/geography)
* [Root for geography downloads and documentation](https://www12.statcan.gc.ca/census-recensement/2016/geo/index-eng.cfm) 
* [Direct link to download directory for 2016 shapefiles](https://www12.statcan.gc.ca/census-recensement/2011/geo/bound-limit/bound-limit-2016-eng.cfm)
* [Heirarchy of geography](https://www150.statcan.gc.ca/n1/pub/92-195-x/2011001/other-autre/hierarch/h-eng.htm)


### Parsing the filename for metadata

Suppose you've downloaded the geography file ```lpr_000a16a_e.zip```. The filename defines the important geographic characteristics of the file (you can process using the ```code_pos``` dataset for code positions, or ```geo_info```).

```r
str(geo_info("lpr_000a16a_e"))

And each of these codes has a meaning that can be found (sometimes) in the geography guide that accompanies a downloaded file (but you can't find out the details until after you've downloaded it, and is missing some information).

Your first default parameters should be:

• file_type == "a" (digital boundary file---it doesn't look as good but it's smaller)
• format == "a" (ArcGIS/ArcInfo®/.shp---for use with sf and other R geographic packages)
• geo_coverage == "000" (Canada---the only option AFAIK)
• projection == "g" (geographic projection/lat-long---this makes it less likely for the user to get caught up in coordinate reference systems [CRS] conversion issues)

The most important choices for the user are: year (2016 is the latest census year currently available), language (english or french) and geo_code/geo_level. A list of geo codes and geo levels are given in the code_book dataset:

{r geos} dplyr::filter(code_book, code_type == "geo_level")

Business data usually isn't released below the economic region level (er_), while census data can go down to census tract (ct_), dissemination area (da_) or dissemination block (db_).

English and french maps are in different files, so they have different codes: lpr_000a16a_e.zip has the english province/territory maps and lpr_000a16a_f.zip has the french province/territory maps. The only difference, AFAIK, is that the guide and geography names are in french in the french version.

Notes & Other Packages

There are some other great packages to make Canadian maps!

• cancensus (R package available from CRAN + github)
• censusmapper.ca (from the same ppl as ^, but a website)
• rcanvec (R package to get v cool NTS maps, good for small scales)

And others probably! openstreetmap and osmdata and leaflet are all useful as well.

Please note that the 'canmap' project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

tweed1e/canmap documentation built on Dec. 21, 2024, 3:19 p.m.