Open and merge multiple shapefiles

or more precisely union many spatial tables in R in a tidy way.

This post is a mess. See the updated version.

  • dplyr::bind_rows doesn’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 use*.

→ 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$") %>% 

or now in 2023, because map_dfr() is being superseded :

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

As of October 2019 this method doesn’t work any longer, due to an update in the vctrs package.
So your best bet is to have the same structure in your shapefile and use :

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

It works again with vctrs 0.2.2 (February 2020)

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



url <-  c("",

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() %>%

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

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

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

* We could have used

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

but the column structure doesn’t match here…

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