Download the datasets

Here are all the goodies!

The most recent, consistent, and complete datasets are probably the following:

• dataset based on LAU for 2020, NUTS for 2016, population-grid for 2018, available following this link.
• dataset based on LAU for 2020, NUTS for 2021, population-grid for 2018, available following this link.

The same files are available also as releases on GitHub, which makes it even easier to download them or include reference to them in scripts (see below). This is, for example, the direct download link for the

https://github.com/EDJNet/lau_centres/releases/download/lau_2020_nuts_2021_pop_grid_2018/lau_2020_nuts_2021_pop_2018_p_2_adjusted_intersection.csv

All files used for matching LAU and NUTS by geometry are in the lau_nuts_area folder.

Concordance tables based on either official concordance tables or geometry are available in this folder: lau_nuts_concordance_combo folder.

Get the data from R

You can read the dataset directly from the source, e.g. with something like:

library("readr")
read_csv(file = "https://github.com/EDJNet/lau_centres/releases/download/lau_2020_nuts_2021_pop_grid_2018/lau_2020_nuts_2021_pop_2018_p_2_adjusted_intersection.csv")

If you prefer to be explicit about column types:

read_csv(file = "https://github.com/EDJNet/lau_centres/releases/download/lau_2020_nuts_2021_pop_grid_2018/lau_2020_nuts_2021_pop_2018_p_2_adjusted_intersection.csv",
         col_types = cols(
           gisco_id = col_character(),
           longitude = col_double(),
           latitude = col_double(),
           country = col_character(),
           nuts_2 = col_character(),
           nuts_3 = col_character(),
           lau_id = col_character(),
           lau_name = col_character(),
           population = col_double(),
           area_km2 = col_double(),
           year = col_double(),
           fid = col_character(),
           concordance = col_character(),
           pop_weighted = col_logical()
         ))

You can also use the package piggyback if you want to include this in your scripts, without worrying about caching. The following will download the file only if it does not exist locally:

library("piggyback")


pb_download(file = "lau_2020_nuts_2021_pop_2018_p_2_adjusted_intersection.csv",
            repo = "EDJNet/lau_centres",
            tag = "lau_2020_nuts_2021_pop_grid_2018")


read_csv(file = "lau_2020_nuts_2021_pop_2018_p_2_adjusted_intersection.csv",
         col_types = cols(
           gisco_id = col_character(),
           longitude = col_double(),
           latitude = col_double(),
           country = col_character(),
           nuts_2 = col_character(),
           nuts_3 = col_character(),
           lau_id = col_character(),
           lau_name = col_character(),
           population = col_double(),
           area_km2 = col_double(),
           year = col_double(),
           fid = col_character(),
           concordance = col_character(),
           pop_weighted = col_logical()
         ))

You can change the year of LAU and NUTS to obtain the desired version.