Title: Convert European Regional Data
Version: 1.1.0
Description: Motivated by changing administrative boundaries over time, the 'nuts' package can convert European regional data with NUTS codes between versions (2006, 2010, 2013, 2016 and 2021) and levels (NUTS 1, NUTS 2 and NUTS 3). The package uses spatial interpolation as in Lam (1983) <doi:10.1559/152304083783914958> based on granular (100m x 100m) area, population and land use data provided by the European Commission's Joint Research Center.
License: MIT + file LICENSE
URL: https://docs.ropensci.org/nuts/, https://github.com/ropensci/nuts
BugReports: https://github.com/ropensci/nuts
Depends: R (≥ 3.5.0)
Imports: cli, dplyr, glue, lifecycle, rlang
Suggests: distill, eurostat, formatR, ggalluvial, ggfittext, ggplot2, ggpubr, ggrepel, gridExtra, kableExtra, knitr, raster, RColorBrewer, readr, rmarkdown, sf, stringr, terra, testthat, tidyr, withr
VignetteBuilder: knitr
Config/testthat/edition: 3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.1
NeedsCompilation: no
Packaged: 2024-07-13 10:35:53 UTC; moritz
Author: Moritz Hennicke ORCID iD [aut, cre, cph], Werner Krause ORCID iD [aut, cph], Pueyo-Ros Josep [rev] (Josep reviewed the package for rOpenSci, see https://github.com/ropensci/software-review/issues/623#issuecomment-1951446662), Le Meur Nolwenn [rev] (Nolwenn reviewed the package for rOpenSci, see https://github.com/ropensci/software-review/issues/623#issuecomment-1961501137)
Maintainer: Moritz Hennicke <AAoritz@posteo.de>
Repository: CRAN
Date/Publication: 2024-07-13 10:50:02 UTC

nuts: Convert European Regional Data

Description

logo

Motivated by changing administrative boundaries over time, the 'nuts' package can convert European regional data with NUTS codes between versions (2006, 2010, 2013, 2016 and 2021) and levels (NUTS 1, NUTS 2 and NUTS 3). The package uses spatial interpolation as in Lam (1983) doi:10.1559/152304083783914958 based on granular (100m x 100m) area, population and land use data provided by the European Commission's Joint Research Center.

Author(s)

Maintainer: Moritz Hennicke AAoritz@posteo.de (ORCID) [copyright holder]

Authors:

Other contributors:

See Also

Useful links:

List of all NUTS codes and classifications

Description

The data frame stores all NUTS codes in hierarchical levels 1, 2 and 3 by NUTS classification versions 2006, 2010, 2013, 2016 and 2021.

Usage

all_nuts_codes

Format

all_nuts_codes

A data frame with 8,896 rows and 2 columns:

code

NUTS code

version

NUTS versions

country

Country name

Source

https://urban.jrc.ec.europa.eu/tools/nuts-converter?lng=en#/

Conversion table provided by the Joint Research Center of the European Commission

Description

The table contains population, area and surface flows between two NUTS regions and different NUTS code classifications. NUTS regions are at 1st, 2nd and 3rd level. NUTS versions are 2006, 2010, 2013, 2016 and 2021.

Usage

cross_walks

Format

cross_walks

A data frame with 47,340 rows and 9 columns:

from_code

Departing NUTS code

to_code

Desired NUTS code

from_version

Departing NUTS version

to_version

Desired NUTS version

level

NUTS division level

country

Country name

areaKm

Area size flow

pop18

2018 population flow

pop11

2011 population flow

artif_surf18

2018 artificial surfaces flow

artif_surf12

2012 artificial surfaces flow

Source

https://urban.jrc.ec.europa.eu/tools/nuts-converter?lng=en#/

Manure storage facilities by NUTS 3 regions from Eurostat (aei_fm_ms)

Description

The data frame contains the number of different manure storage facilities from the Farm Structure Survey in all (former) EU member states, such as Iceland, Norway, Switzerland and Montenegro at the NUTS 3 level. Please see the link indicated below for more information.

Usage

manure

Format

manure

A data frame with 17,151 rows and 4 columns:

indic_ag

9 indicators: All manure storage facilities, solid dung, liquid manure slurry, slurry: tank, slurry: lagoon; covered facilities with either dung, liquid manure, slurry

geo

NUTS 1, 2, 3 or National level

time

Years 2000, 2003 and 2010

values

Number

Source

https://ec.europa.eu/eurostat/databrowser/view/aei_fm_ms/default/table?lang=en

Aggregate to higher order NUTS levels

Description

nuts_aggregate() transforms regional NUTS data between NUTS levels.

Usage

nuts_aggregate(
  data,
  to_level,
  variables,
  weight = NULL,
  missing_rm = FALSE,
  missing_weights_pct = FALSE,
  multiple_versions = c("error", "most_frequent")
)

Arguments

data

A nuts.classified object returned by nuts_classify().

to_level

Number corresponding to the desired NUTS level to be aggregated to: 1 or 2.

variables

Named character specifying variable names and variable type ('absolute' or 'relative'), e.g. c('var_name' = 'absolute').

weight

String with name of the weight used for conversion. Can be area size 'areaKm' (default), population in 2011 'pop11' or 2018 'pop18', or artificial surfaces in 2012 'artif_surf12' and 2018 'artif_surf18'.

missing_rm

Boolean that is FALSE by default. TRUE removes regional flows that depart from missing NUTS codes.

missing_weights_pct

Boolean that is FALSE by default. TRUE computes the percentage of missing weights due to missing departing NUTS regions for each variable.

multiple_versions

By default equal to 'error', when providing multiple NUTS versions within groups. If set to 'most_frequent' data is converted using the best-matching NUTS version.

Details

Console messages can be controlled with rlang::local_options(nuts.verbose = "quiet") to silence messages and nuts.verbose = "verbose" to switch messages back on.

Value

A tibble containing NUTS codes, aggregated variable values, and possibly grouping variables.

Examples

library(dplyr)

# Load EUROSTAT data of manure storage deposits
data(manure)

# Data varies at the NUTS level x indicator x year x country x NUTS code level
head(manure)

# Aggregate from NUTS 3 to 2 by indicator x year
manure %>%
  filter(nchar(geo) == 5) %>%
  nuts_classify(nuts_code = "geo",
                group_vars = c('indic_ag','time')) %>%
  # Group vars are automatically passed on
  nuts_aggregate(to_level = 2,
                 variables = c('values'= 'absolute'),
                 weight = 'pop18')

Classify version of NUTS codes

Description

nuts_classify() can identify the NUTS version year and level from a variable containing NUTS codes.

Usage

nuts_classify(
  data,
  nuts_code,
  group_vars = NULL,
  ties = c("most_recent", "oldest")
)

Arguments

data

A data frame or tibble that contains a variable with NUTS 1, 2 or 3 codes and possibly other variables. NUTS codes must be of the same level and need to be unique, unless additional grouping variables are specified. No duplicate NUTS codes within groups allowed.

nuts_code

Variable name containing NUTS codes

group_vars

Variable name(s) for classification within groups. nuts_classify() always computes overlap within country. Hence, country variables should not be specified. NULL by default.

ties

Picks 'most_recent' or 'oldest' version when overlap is identical across multiple NUTS versions. 'most_recent' by default.

Details

Console messages can be controlled with rlang::local_options(nuts.verbose = "quiet") to silence messages and nuts.verbose = "verbose" to switch messages back on.

Value

A list of three tibbles. The first tibble contains the original data with the classified NUTS version, level, and country. The second tibble lists the group-specific overlap with each NUTS version. The third tibble shows missing NUTS codes for each group.

The output can be passed to nuts_convert_version() to convert data across NUTS versions and nuts_aggregate() to aggregate across NUTS levels.

Examples

library(dplyr)

# Load EUROSTAT data of manure storage deposits
data(manure)

# Data varies at the NUTS level x indicator x year x country x NUTS code level
head(manure)

# Classify version of NUTS 2 codes in Germany
manure %>%
 filter(nchar(geo) == 4) %>%
 filter(indic_ag == 'I07A_EQ_Y') %>%
 filter(grepl('^DE', geo)) %>%
 filter(time == 2003) %>%
 select(-indic_ag, -time) %>%
 # Data varies at the NUTS code level
 nuts_classify(nuts_code = 'geo')

# Classify version of NUTS 3 codes within country and year
manure %>%
  filter(nchar(geo) == 5) %>%
  filter(indic_ag == 'I07A_EQ_Y') %>%
  select(-indic_ag) %>%
  # Data varies at the year x country x NUTS code level. The country grouping
  # is always used by default.
  nuts_classify(nuts_code = 'geo', group_vars = 'time')

Convert between NUTS versions

Description

nuts_convert_version() transforms regional NUTS data between NUTS versions.

Usage

nuts_convert_version(
  data,
  to_version,
  variables,
  weight = NULL,
  missing_rm = FALSE,
  missing_weights_pct = FALSE,
  multiple_versions = c("error", "most_frequent")
)

Arguments

data

A nuts.classified object returned by nuts_classify().

to_version

String with desired NUTS version the function should convert to. Possible versions: '2006', '2010', '2013', '2016' or '2021'

variables

Named character specifying variable names and variable type ('absolute' or 'relative') e.g. c('var_name' = 'absolute')

weight

String with name of the weight used for conversion. Can be area size 'areaKm' (default), population in 2011 'pop11' or 2018 'pop18', or artificial surfaces in 2012 'artif_surf12' and 2018 'artif_surf18'.

missing_rm

Boolean that is FALSE by default. TRUE removes regional flows that depart from missing NUTS codes.

missing_weights_pct

Boolean that is FALSE by default. TRUE computes the percentage of missing weights due to missing departing NUTS regions for each variable.

multiple_versions

By default equal to 'error', when providing multiple NUTS versions within groups. If set to 'most_frequent' data is converted using the best-matching NUTS version.

Details

Console messages can be controlled with rlang::local_options(nuts.verbose = "quiet") to silence messages and nuts.verbose = "verbose" to switch messages back on.

Value

A tibble containing NUTS codes, converted variable values, and possibly grouping variables.

Examples

library(dplyr)

# Load EUROSTAT data of manure storage deposits
data(manure)

# Data varies at the NUTS level x indicator x year x country x NUTS code level
head(manure)

# Convert NUTS 2 codes in Germany from 2006 to 2021 version
manure %>%
  filter(nchar(geo) == 4) %>%
  filter(indic_ag == 'I07A_EQ_Y') %>%
  filter(grepl('^DE', geo)) %>%
  filter(time == 2003) %>%
  select(-indic_ag, -time) %>%
  # Data now only varies at the NUTS code level
  nuts_classify(nuts_code = "geo") %>%
  nuts_convert_version(to_version = '2021',
                       weight = 'pop18',
                       variables = c('values' = 'absolute'))


# Convert NUTS 3 codes by country x year, classifying version first
manure %>%
  filter(nchar(geo) == 5) %>%
  filter(indic_ag == 'I07A_EQ_Y') %>%
  select(-indic_ag) %>%
  # Data now varies at the year x NUTS code level
  nuts_classify(nuts_code = 'geo', group_vars = c('time')) %>%
  nuts_convert_version(to_version = '2021',
                       weight = 'pop18',
                       variables = c('values' = 'absolute'))

Return classified NUTS data

Description

nuts_get_data() returns the classified data after running nuts_classify().

Usage

nuts_get_data(data)

Arguments

data

A nuts.classified object returned by nuts_classify().

Details

Console messages can be controlled with rlang::local_options(nuts.verbose = "quiet") to silence messages and nuts.verbose = "verbose" to switch messages back on.

Value

A tibble containing the original data with the classified NUTS version, level, and country.

Examples

library(dplyr)

# Load EUROSTAT data of manure storage deposits
data(manure)

# Classify version of NUTS 2 codes in Germany
classified <- manure %>%
   filter(nchar(geo) == 4) %>%
   filter(indic_ag == 'I07A_EQ_Y') %>%
   filter(grepl('^DE', geo)) %>%
   filter(time == 2003) %>%
   select(-indic_ag, -time) %>%
   # Data varies at the NUTS code level
   nuts_classify(nuts_code = 'geo')

nuts_get_data(classified)

Return missing NUTS codes in classified NUTS data

Description

nuts_get_missing() returns the classified data after running nuts_classify().

Usage

nuts_get_missing(data)

Arguments

data

A nuts.classified object returned by nuts_classify().

Details

Console messages can be controlled with rlang::local_options(nuts.verbose = "quiet") to silence messages and nuts.verbose = "verbose" to switch messages back on.

Value

A tibble listing missing NUTS codes for each group.

Examples

library(dplyr)

# Load EUROSTAT data of manure storage deposits
data(manure)

# Classify version of NUTS 2 codes in Germany
classified <- manure %>%
   filter(nchar(geo) == 4) %>%
   filter(indic_ag == 'I07A_EQ_Y') %>%
   filter(grepl('^DE', geo)) %>%
   filter(time == 2003) %>%
   select(-indic_ag, -time) %>%
   # Data varies at the NUTS code level
   nuts_classify(nuts_code = 'geo')

nuts_get_missing(classified)

Return version overlap of classified NUTS data

Description

nuts_get_version() returns the classified data after running nuts_classify().

Usage

nuts_get_version(data)

Arguments

data

A nuts.classified object returned by nuts_classify().

Details

Console messages can be controlled with rlang::local_options(nuts.verbose = "quiet") to silence messages and nuts.verbose = "verbose" to switch messages back on.

Value

A tibble that lists the group-specific overlap with each NUTS version.

Examples

library(dplyr)

# Load EUROSTAT data of manure storage deposits
data(manure)

# Classify version of NUTS 2 codes in Germany
classified <- manure %>%
   filter(nchar(geo) == 4) %>%
   filter(indic_ag == 'I07A_EQ_Y') %>%
   filter(grepl('^DE', geo)) %>%
   filter(time == 2003) %>%
   select(-indic_ag, -time) %>%
   # Data varies at the NUTS code level
   nuts_classify(nuts_code = 'geo')

nuts_get_version(classified)

Helper function to test for multiple versions

Description

nuts_test_multiple_versions is called from either nuts_convert_version or nuts_aggregate to selects the most frequent version within groups or throw an error.

Usage

nuts_test_multiple_versions(group_vars, multiple_versions, data_versions, data)

Arguments

group_vars

Variable name(s) for classification within groups. Always computes overlap within country. NULL by default.

multiple_versions

By default equal to 'error', when providing multiple NUTS versions within groups.

data_versions

Data versions

data

A nuts.classified object returned by nuts_classify().

Value

A tibble containing NUTS codes, the potential number of rows dropped and a message with the results of the test.

Examples

library(dplyr)
df <- manure %>%
  filter(nchar(geo) == 5) %>%
  select(geo, indic_ag, values) %>%
  distinct(geo,  .keep_all = TRUE) %>%
  nuts_classify(nuts_code = "geo",
                group_vars = "indic_ag",
                data = .)

nuts_test_multiple_versions(group_vars = "indic_ag",
                            multiple_versions = "most_frequent",
                            data_versions = df$versions_data,
                            data = df$data)

Patent applications to the EPO by priority year by NUTS 3 regions (pat_ep_rtot)

Description

The data frame contains information on patent applications to the European Patent Office by year and NUTS 3 regions.

Usage

patents

Format

patents

A data frame with 104,106 rows and 4 columns:

unit

4 indicators: Number, Nominal GDP in billion euro, Per million habitants, Per million of population in the labor force

geo

NUTS 1, 2, 3 or National level

time

Years 2008, 2009, 2010, 2011 and 2012

values

Values

Source

https://ec.europa.eu/eurostat/databrowser/view/PAT_EP_RTOT/default/table