Open and merge multiple shapefiles

This post is a mess. See the updated version.

~~dplyr::bind_rowsdoesn’t work on {sf} objects~~ (it seems that as of 2020-12-27, it works);
base::rbind needs the objects to have the same structure and only works on two tables and so that’s not straightforward to use¹.

→ So we’ll use purrr::map and tidyr::unnest.

NB : now in 2021, I advise to simply use:

 fs::dir_ls("my_folder", regexp = ".*\\.shp$") %>% 
    purrr::map_dfr(sf::read_sf)

or now in 2023, because map_dfr() is being superseded:

fs::dir_ls("my_folder", regexp = ".*\\.shp$") %>% 
  purrr::map(sf::read_sf) %>% 
  dplyr::bind_rows()

dir_ls("my_folder", regexp = ".*\\.shp$") %>% 
  purrr::map(sf:::read_sf) %>%
  purrr::list_rbind() %>%
  sf::st_sf()

As of October 2019 this method doesn’t work any longer, due to an update in the vctrs package.
https://github.com/r-spatial/sf/issues/1172.
So your best bet is to have the same structure in your shapefile and use:

dir_ls("shp", glob = "*.shp") %>%
  map(read_sf) %>%
  do.call(rbind, .)

It works again with vctrs 0.2.2 (February 2020)

First get some data, the communes of three french départements:

library(tidyverse)
library(sf)
library(fs)
library(httr)
library(leaflet)

# https://fr.actualitix.com/blog/shapefiles-des-departements-de-france.html

url <-  c("https://fr.actualitix.com/blog/actgeoshap/01-Ain.zip",
          "https://fr.actualitix.com/blog/actgeoshap/73-savoie.zip",
          "https://fr.actualitix.com/blog/actgeoshap/74-haute-savoie.zip")

dep <- str_extract(url, "\\d{2}.*$")

list(url, dep) %>% 
  pwalk(~ GET(.x, write_disk(.y)))

walk(dep, unzip, junkpaths = TRUE, exdir = "shp")

We can then create a 3 rows data frame containing a list-column in which we store the sf object. Then we just unnest it. This operation erases the sf-class, we have to add it back.

res <- dir_ls("shp", glob = "*.shp") %>% 
  tibble(fname = .) %>%
  mutate(data = map(fname, read_sf)) %>%
  unnest(data) %>%
  st_sf() %>%
  st_set_crs("EPSG:2154")

write_sf(res, "shp/3dep.shp")

res %>% 
  st_transform(4326) %>% 
  leaflet() %>%
    addPolygons() %>% 
    addTiles()

Bonus: we have the source filename stored in the resulting shapefile.

Footnotes

We could have used:

dir_ls("shp", glob = "*.shp") %>%
  map(read_sf) %\>%
  do.call(rbind, .)

but the column structure doesn’t match here…↩︎

--- title: "Open and merge multiple shapefiles" description: "or more precisely union many spatial tables in R in a tidy way" author: "Michaël" date: "2019-03-27" date-modified: last-modified categories: - R - spatial draft: false freeze: true editor_options: chunk_output_type: console chunk_output_type: console execute: eval: false --- This post is a mess. [See the updated version](/posts/2023/open_and_merge_multiple_shapefiles_updated/). - ~~`dplyr::bind_rows`[doesn't work](https://github.com/r-spatial/sf/issues/49) on {sf} objects~~ (it seems that as of 2020-12-27, it works); - `base::rbind` needs the objects to have the same structure and only works on two tables and so that's not straightforward to use[^1]. [^1]: We could have used: ``` r dir_ls("shp", glob = "*.shp") %>% map(read_sf) %\>% do.call(rbind, .) ``` but the column structure doesn't match here... → So we'll use `purrr::map` and `tidyr::unnest`. **NB : now in 2021, I advise to simply use:** ```{r} fs::dir_ls("my_folder", regexp = ".*\\.shp$") %>% purrr::map_dfr(sf::read_sf) ``` or **now in 2023**, because `map_dfr()` is being superseded: ```{r} fs::dir_ls("my_folder", regexp = ".*\\.shp$") %>% purrr::map(sf::read_sf) %>% dplyr::bind_rows() ``` ```{r} dir_ls("my_folder", regexp = ".*\\.shp$") %>% purrr::map(sf:::read_sf) %>% purrr::list_rbind() %>% sf::st_sf() ``` ------------------------------------------------------------------------ ~~As of October 2019 this method doesn't work any longer, due to an update in the vctrs package.\ <https://github.com/r-spatial/sf/issues/1172>.\ So your best bet is to have the same structure in your shapefile and use:~~ ```{r} dir_ls("shp", glob = "*.shp") %>% map(read_sf) %>% do.call(rbind, .) ``` It works again with vctrs 0.2.2 (February 2020) ------------------------------------------------------------------------ First get some data, the communes of three french départements: ```{r} library(tidyverse) library(sf) library(fs) library(httr) library(leaflet) # https://fr.actualitix.com/blog/shapefiles-des-departements-de-france.html url <- c("https://fr.actualitix.com/blog/actgeoshap/01-Ain.zip", "https://fr.actualitix.com/blog/actgeoshap/73-savoie.zip", "https://fr.actualitix.com/blog/actgeoshap/74-haute-savoie.zip") dep <- str_extract(url, "\\d{2}.*$") list(url, dep) %>% pwalk(~ GET(.x, write_disk(.y))) walk(dep, unzip, junkpaths = TRUE, exdir = "shp") ``` We can then create a 3 rows data frame containing a list-column in which we store the sf object. Then we just unnest it. This operation erases the sf-class, we have to add it back. ```{r} res <- dir_ls("shp", glob = "*.shp") %>% tibble(fname = .) %>% mutate(data = map(fname, read_sf)) %>% unnest(data) %>% st_sf() %>% st_set_crs("EPSG:2154") write_sf(res, "shp/3dep.shp") res %>% st_transform(4326) %>% leaflet() %>% addPolygons() %>% addTiles() ``` ![](images/Capture-du-2019-03-27-22-17-52.png) Bonus: we have the source filename stored in the resulting shapefile.