datasets.Rmd

---
title: "Download the datasets"
description: |
  Here are all the goodies!
author:
  - name: Giorgio Comai 
    url: https://giorgiocomai.eu
    affiliation: OBCT/EDJNet
    affiliation_url: https://www.europeandatajournalism.eu/
date: "`r Sys.Date()`"
---

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](https://github.com/EDJNet/lau_centres/tree/main/lau_centres/lau_2020_nuts_2016_pop_2018_p_2_adjusted_intersection.csv).
- dataset based on LAU for 2020, NUTS for 2021, population-grid for 2018, available [following this link](https://github.com/EDJNet/lau_centres/tree/main/lau_centres/lau_2020_nuts_2021_pop_2018_p_2_adjusted_intersection.csv).


The same files are available also [as releases on GitHub](https://github.com/EDJNet/lau_centres/releases), 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`](https://github.com/EDJNet/lau_centres/tree/main/lau_nuts_area) folder.

Concordance tables based on either official concordance tables or geometry are available in this folder: [`lau_nuts_concordance_combo`](https://github.com/EDJNet/lau_centres/tree/main/lau_nuts_concordance_combo) folder.


## Get the data from R


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

```{r eval = FALSE}
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:

```{r eval = FALSE}
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:

```{r eval = FALSE}
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.