diff --git a/pkgdown.yml b/pkgdown.yml index 3d9be41..a4e2554 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -2,7 +2,7 @@ pandoc: 3.1.11 pkgdown: 2.1.1 pkgdown_sha: ~ articles: {} -last_built: 2024-12-16T10:44Z +last_built: 2024-12-16T10:48Z urls: reference: http://www.ekotov.pro/mapineqr/reference article: http://www.ekotov.pro/mapineqr/articles diff --git a/reference/mi_data.html b/reference/mi_data.html index e95c036..a7aa28e 100644 --- a/reference/mi_data.html +++ b/reference/mi_data.html @@ -78,13 +78,11 @@

Argumentsx_filters -

A named list where the names are the filter fields for the x variable -and the values are the selected values for those fields. Default is an empty list.

+

A named list where the names are the filter fields for the x variable and the values are the selected values for those fields. Default is an empty list. To find out which filters to use, use mi_source_filters with the desired source_name.

y_filters
-

(Optional) A named list where the names are the filter fields for the y variable -and the values are the selected values for those fields. Default is NULL.

+

(Optional) A named list where the names are the filter fields for the y variable and the values are the selected values for those fields. Default is NULL. To find out which filters to use, use mi_source_filters with the desired source_name.

limit
diff --git a/search.json b/search.json index 4a8e5c5..5e59e07 100644 --- a/search.json +++ b/search.json @@ -1 +1 @@ -[{"path":"http://www.ekotov.pro/mapineqr/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2024 mapineqr authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"http://www.ekotov.pro/mapineqr/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Egor Kotov. Author, maintainer.","code":""},{"path":"http://www.ekotov.pro/mapineqr/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Kotov E (2024). mapineqr. Access Mapineq inequality indicators via API. doi:10.32614/CRAN.package.mapineqr, https://github.com/e-kotov/mapineqr. Mills M, Leasure D (2024). “Mapineq Link: Geospatial Dashboard Database.” doi:10.5281/zenodo.13864000.","code":"@Manual{mapineqr, title = {mapineqr. Access Mapineq inequality indicators via API}, author = {Egor Kotov}, year = {2024}, url = {https://github.com/e-kotov/mapineqr}, doi = {10.32614/CRAN.package.mapineqr}, } @Misc{mapineq_link, title = {Mapineq Link: Geospatial Dashboard and Database}, author = {Melinda C Mills and Douglas Leasure}, year = {2024}, month = {October}, publisher = {Mapineq deliverables. Turku: INVEST Research Flagship Centre / University of Turku}, doi = {10.5281/zenodo.13864000}, }"},{"path":"http://www.ekotov.pro/mapineqr/index.html","id":"mapineqr","dir":"","previous_headings":"","what":"Access Mapineq inequality indicators via API","title":"Access Mapineq inequality indicators via API","text":"R package access data https://www.mapineq.org/ API dashboard (product Mapineq proejct)","code":""},{"path":"http://www.ekotov.pro/mapineqr/index.html","id":"mapineqr-1","dir":"","previous_headings":"","what":"mapineqr","title":"Access Mapineq inequality indicators via API","text":"goal mapineqr access data Mapineq.org API dashboard (product Mapineq proejct).","code":""},{"path":"http://www.ekotov.pro/mapineqr/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Access Mapineq inequality indicators via API","text":"can install development version mapineqr GitHub :","code":"if (!require(\"pak\")) install.packages(\"pak\") pak::pak(\"e-kotov/mapineqr\") # load packages used in the examples on this page library(mapineqr) library(dplyr) library(ggplot2) library(eurostat) library(sf) library(biscale)"},{"path":"http://www.ekotov.pro/mapineqr/index.html","id":"basic-example---univariate-data-and-maps","dir":"","previous_headings":"","what":"Basic Example - univariate data and maps","title":"Access Mapineq inequality indicators via API","text":"Get full list available data NUTS 3 level: Select data source source_name column check ’s year NUTS level coverage: Check available filters data source: Choose indicator filter (let burglaries) get data: Map indicator using NUTS2 polygons:","code":"library(mapineqr) available_data <- mi_sources(level = \"3\") head(available_data) # A tibble: 52 × 3 source_name short_description description 1 DEMO_R_D3AREA \"Area by NUTS 3 regio\" Area by NUTS 3 region (ESTAT) 2 PROJ_19RAASFR3 \"Assumptions for fert\" Assumptions for fertility rates by age, type of projection and NUTS… 3 PROJ_19RAASMR3 \"Assumptions for prob\" Assumptions for probability of dying by age, sex, type of projectio… 4 BD_HGNACE2_R3 \"Business demography \" Business demography and high growth enterprise by NACE Rev. 2 and N… 5 BD_SIZE_R3 \"Business demography \" Business demography by size class and NUTS 3 regions (ESTAT) 6 CENS_11DWOB_R3 \"Conventional dwellin\" Conventional dwellings by occupancy status, type of building and NU… 7 CRIM_GEN_REG \"Crimes recorded by t\" Crimes recorded by the police by NUTS 3 regions (ESTAT) 8 DEMO_R_MAGEC3 \"Deaths by age group,\" Deaths by age group, sex and NUTS 3 region (ESTAT) 9 DEMO_R_MWK3_T \"Deaths by week and N\" Deaths by week and NUTS 3 region (ESTAT) 10 DEMO_R_MWK3_TS \"Deaths by week, sex \" Deaths by week, sex and NUTS 3 region (ESTAT) # ℹ 42 more rows # ℹ Use `print(n = ...)` to see more rows mi_source_coverage(\"CRIM_GEN_REG\") # A tibble: 10 × 5 nuts_level year source_name short_description description 1 0 2008 CRIM_GEN_REG Crimes recorded by t Crimes recorded by the police by NUTS 3 regions (ESTAT) 2 0 2009 CRIM_GEN_REG Crimes recorded by t Crimes recorded by the police by NUTS 3 regions (ESTAT) 3 0 2010 CRIM_GEN_REG Crimes recorded by t Crimes recorded by the police by NUTS 3 regions (ESTAT) 4 1 2008 CRIM_GEN_REG Crimes recorded by t Crimes recorded by the police by NUTS 3 regions (ESTAT) 5 1 2009 CRIM_GEN_REG Crimes recorded by t Crimes recorded by the police by NUTS 3 regions (ESTAT) 6 1 2010 CRIM_GEN_REG Crimes recorded by t Crimes recorded by the police by NUTS 3 regions (ESTAT) 7 2 2008 CRIM_GEN_REG Crimes recorded by t Crimes recorded by the police by NUTS 3 regions (ESTAT) 8 2 2009 CRIM_GEN_REG Crimes recorded by t Crimes recorded by the police by NUTS 3 regions (ESTAT) 9 2 2010 CRIM_GEN_REG Crimes recorded by t Crimes recorded by the police by NUTS 3 regions (ESTAT) 10 3 2008 CRIM_GEN_REG Crimes recorded by t Crimes recorded by the police by NUTS 3 regions (ESTAT) mi_source_filters(\"CRIM_GEN_REG\", year = 2010, level = \"2\") # A tibble: 6 × 4 field field_label label value 1 unit Unit of measure Number NR 2 freq Time frequency Annual A 3 iccs International classification of crime for statistical purposes (ICCS) Intentional homicide ICCS0101 4 iccs International classification of crime for statistical purposes (ICCS) Robbery ICCS0401 5 iccs International classification of crime for statistical purposes (ICCS) Burglary of private residential premises ICCS05012 6 iccs International classification of crime for statistical purposes (ICCS) Theft of a motorized land vehicle ICCS050211 x <- mi_data(x_source = \"CRIM_GEN_REG\", year = 2010, level = \"2\", x_filters = list(iccs = \"ICCS05012\")) head(x) # A tibble: 6 × 4 best_year geo geo_name x 1 2008 AT11 Burgenland (A) 223 2 2008 AT12 Niederösterreich 2557 3 2008 AT13 Wien 9319 4 2008 AT21 Kärnten 507 5 2008 AT22 Steiermark 1163 6 2008 AT31 Oberösterreich 988 library(eurostat) library(ggplot2) # load NUTS2 level polygons nuts2 <- eurostat::get_eurostat_geospatial(nuts_level = 2, year = \"2010\", crs = \"4326\") # join data to NUTS2 polygons nuts2_crime <- nuts2 |> left_join(x, by = \"geo\") # plot a map of burglaries map_burglaries <- ggplot(nuts2_crime) + geom_sf(aes(fill = x)) + scale_fill_viridis_c() + labs(title = \"Number of burglaries of private residential premises in 2010\") + theme_minimal() ggsave(\"man/figures/map_burglaries.png\", map_burglaries, width = 8, height = 6, dpi = 200, create.dir = TRUE)"},{"path":"http://www.ekotov.pro/mapineqr/index.html","id":"advanced-example---bivariate-data-and-maps","dir":"","previous_headings":"","what":"Advanced Example - bivariate data and maps","title":"Access Mapineq inequality indicators via API","text":"Select two indicators. Let (1) unemployment rate: (2) life expectancy: Check available filters: Get data two indicators: Plot scratterplot: Add bivariate data NUTS2 polygons create plot:","code":"mi_source_coverage(\"TGS00010\") |> dplyr::arrange(desc(year)) # A tibble: 12 × 5 nuts_level year source_name short_description description 1 2 2022 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) 2 2 2021 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) 3 2 2020 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) 4 2 2019 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) 5 2 2018 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) 6 2 2017 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) 7 2 2016 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) 8 2 2015 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) 9 2 2014 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) 10 2 2013 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) 11 2 2012 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) 12 2 2011 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) mi_source_coverage(\"DEMO_R_MLIFEXP\") |> dplyr::arrange(desc(year)) # A tibble: 96 × 5 nuts_level year source_name short_description description 1 0 2021 DEMO_R_MLIFEXP Life expectancy by a Life expectancy by age, sex and NUTS 2 region (ESTAT) 2 1 2021 DEMO_R_MLIFEXP Life expectancy by a Life expectancy by age, sex and NUTS 2 region (ESTAT) 3 2 2021 DEMO_R_MLIFEXP Life expectancy by a Life expectancy by age, sex and NUTS 2 region (ESTAT) 4 0 2020 DEMO_R_MLIFEXP Life expectancy by a Life expectancy by age, sex and NUTS 2 region (ESTAT) 5 1 2020 DEMO_R_MLIFEXP Life expectancy by a Life expectancy by age, sex and NUTS 2 region (ESTAT) 6 2 2020 DEMO_R_MLIFEXP Life expectancy by a Life expectancy by age, sex and NUTS 2 region (ESTAT) 7 0 2019 DEMO_R_MLIFEXP Life expectancy by a Life expectancy by age, sex and NUTS 2 region (ESTAT) 8 1 2019 DEMO_R_MLIFEXP Life expectancy by a Life expectancy by age, sex and NUTS 2 region (ESTAT) 9 2 2019 DEMO_R_MLIFEXP Life expectancy by a Life expectancy by age, sex and NUTS 2 region (ESTAT) 10 0 2018 DEMO_R_MLIFEXP Life expectancy by a Life expectancy by age, sex and NUTS 2 region (ESTAT) # ℹ 86 more rows # ℹ Use `print(n = ...)` to see more rows mi_source_filters(\"TGS00010\", year = 2018, level = \"2\") # A tibble: 12 × 4 field field_label label value 1 unit Unit of measure Percentage PC 2 isced11 International Standard Classification of Education (ISCED 2011) All ISCED 2011 levels TOTAL 3 isced11 International Standard Classification of Education (ISCED 2011) Less than primary, primary and lower secondary education (levels 0-2) ED0-2 4 isced11 International Standard Classification of Education (ISCED 2011) Upper secondary and post-secondary non-tertiary education (levels 3 and 4) ED3_4 5 isced11 International Standard Classification of Education (ISCED 2011) Tertiary education (levels 5-8) ED5-8 6 isced11 International Standard Classification of Education (ISCED 2011) Unknown UNK 7 isced11 International Standard Classification of Education (ISCED 2011) No response NRP 8 sex Sex Total T 9 sex Sex Males M 10 sex Sex Females F 11 freq Time frequency Annual A 12 age Age class 15 years or over Y_GE15 mi_source_filters(\"DEMO_R_MLIFEXP\", year = 2018, level = \"2\") |> print(n=90) # A tibble: 91 × 4 field field_label label value 1 unit Unit of measure Year YR 2 sex Sex Total T 3 sex Sex Males M 4 sex Sex Females F 5 freq Time frequency Annual A 6 age Age class Less than 1 year Y_LT1 7 age Age class 1 year Y1 8 age Age class 2 years Y2 9 age Age class 3 years Y3 10 age Age class 4 years Y4 11 age Age class 5 years Y5 12 age Age class 6 years Y6 13 age Age class 7 years Y7 14 age Age class 8 years Y8 15 age Age class 9 years Y9 16 age Age class 10 years Y10 17 age Age class 11 years Y11 ... xy_data <- mi_data( year = 2018, level = \"2\", x_source = \"TGS00010\", x_filters = list(isced11 = \"TOTAL\", unit = \"PC\", age = \"Y_GE15\", sex = \"T\", freq = \"A\"), y_source = \"DEMO_R_MLIFEXP\", y_filters = list(unit = \"YR\", age = \"Y_LT1\", sex = \"T\", freq = \"A\") ) edu_v_life_exp_plot <- ggplot(xy_data, aes(x = x, y = y)) + geom_point() + labs(x = \"Percentage of all adults aged 15 years or over with a degree\", y = \"Life expectancy at birth\") + theme_minimal() # ggsave(\"man/figures/edu_v_life_exp_plot.png\", edu_v_life_exp_plot, width = 8, height = 6, units = \"in\", dpi = 300) nuts2 <- eurostat::get_eurostat_geospatial(nuts_level = 2, year = \"2016\", crs = \"4326\") nuts2_edu_v_life_exp <- nuts2 |> left_join(xy_data, by = \"geo\") library(biscale) bidata <- bi_class(nuts2_edu_v_life_exp, x = x, y = y, style = \"quantile\", dim = 3) legend <- bi_legend(pal = \"GrPink\", dim = 3, xlab = \" Higher % with a degree\", ylab = \" Higher life expectancy\", size = 8) map <- ggplot() + geom_sf(data = bidata, mapping = aes(fill = bi_class), color = \"white\", size = 0.1, show.legend = FALSE) + bi_scale_fill(pal = \"GrPink\", dim = 3) + labs( title = \"Education vs Life Expectancy\" ) + bi_theme() png(\"man/figures/edu_v_life_exp_map.png\", width = 8, height = 6, units = \"in\", res = 300) print(map) print(legend, vp = grid::viewport(x = 0.4, y = .75, width = 0.2, height = 0.2, angle = -45)) dev.off()"},{"path":"http://www.ekotov.pro/mapineqr/index.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Access Mapineq inequality indicators via API","text":"cite R package data publications use: Kotov E (2024). mapineqr. Access Mapineq inequality indicators via API. doi:10.32614/CRAN.package.mapineqr https://doi.org/10.32614/CRAN.package.mapineqr, https://github.com/e-kotov/mapineqr. Mills M, Leasure D (2024). “Mapineq Link: Geospatial Dashboard Database.” doi:10.5281/zenodo.13864000 https://doi.org/10.5281/zenodo.13864000. BibTeX:","code":"@Manual{mapineqr, title = {mapineqr. Access Mapineq inequality indicators via API}, author = {Egor Kotov}, year = {2024}, url = {https://github.com/e-kotov/mapineqr}, doi = {10.32614/CRAN.package.mapineqr}, } @Misc{mapineq_link, title = {Mapineq Link: Geospatial Dashboard and Database}, author = {Melinda C Mills and Douglas Leasure}, year = {2024}, month = {October}, publisher = {Mapineq deliverables. Turku: INVEST Research Flagship Centre / University of Turku}, doi = {10.5281/zenodo.13864000}, }"},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Get univariate or bivariate data for a specific source — mi_data","title":"Get univariate or bivariate data for a specific source — mi_data","text":"Fetches univariate bivariate data given source, year, NUTS level, selected filters.","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get univariate or bivariate data for a specific source — mi_data","text":"","code":"mi_data( x_source, y_source = NULL, year, level, x_filters = list(), y_filters = NULL, limit = 2000 )"},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get univariate or bivariate data for a specific source — mi_data","text":"x_source character string specifying source name x variable. y_source (Optional) character string specifying source name y variable. year character integer specifying year. level character string specifying NUTS level (\"0\", \"1\", \"2\", \"3\"). x_filters named list names filter fields x variable values selected values fields. Default empty list. y_filters (Optional) named list names filter fields y variable values selected values fields. Default NULL. limit integer specifying maximum number results return. Default 2000.","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get univariate or bivariate data for a specific source — mi_data","text":"tibble following columns: univariate data (y_source provided): best_year: best available year, closest requested year. geo: code NUTS region requested level. geo_name: name NUTS region requested level. x: value univariate variable. bivariate data (y_source provided): best_year: best available year, closest requested year (x y variables). geo: code NUTS region requested level. geo_name: name NUTS region requested level. x: value x variable. y: value y variable.","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get univariate or bivariate data for a specific source — mi_data","text":"","code":"if (FALSE) { # \\dontrun{ # Univariate example mi_data( x_source = \"TGS00010\", year = 2020, level = \"2\", x_filters = list(isced11 = \"TOTAL\", unit = \"PC\", age = \"Y_GE15\", freq = \"A\") ) # Bivariate example mi_data( x_source = \"TGS00010\", y_source = \"DEMO_R_MLIFEXP\", year = 2020, level = \"2\", x_filters = list(isced11 = \"TOTAL\", unit = \"PC\", age = \"Y_GE15\", freq = \"A\"), y_filters = list(unit = \"YR\", age = \"Y_LT1\", freq = \"A\") ) } # }"},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_nuts_levels.html","id":null,"dir":"Reference","previous_headings":"","what":"Get a list of available NUTS levels — mi_nuts_levels","title":"Get a list of available NUTS levels — mi_nuts_levels","text":"Get list available NUTS levels","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_nuts_levels.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get a list of available NUTS levels — mi_nuts_levels","text":"","code":"mi_nuts_levels()"},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_nuts_levels.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get a list of available NUTS levels — mi_nuts_levels","text":"character vector valid NUTS levels accepted functions.","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_nuts_levels.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get a list of available NUTS levels — mi_nuts_levels","text":"","code":"if (FALSE) { # \\dontrun{ mi_nuts_levels() } # }"},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_source_coverage.html","id":null,"dir":"Reference","previous_headings":"","what":"Get NUTS level and Year coverage for a specific source — mi_source_coverage","title":"Get NUTS level and Year coverage for a specific source — mi_source_coverage","text":"Get NUTS level Year coverage specific data source.","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_source_coverage.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get NUTS level and Year coverage for a specific source — mi_source_coverage","text":"","code":"mi_source_coverage(source_name, limit = 1500)"},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_source_coverage.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get NUTS level and Year coverage for a specific source — mi_source_coverage","text":"source_name name data source limit integer specifying maximum number results return. Default 2000.","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_source_coverage.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get NUTS level and Year coverage for a specific source — mi_source_coverage","text":"tibble containing following columns: nuts_level: NUTS level year: year source_name: name data source (mathces source_name requested user) short_description: short description data source description: description data source","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_source_coverage.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get NUTS level and Year coverage for a specific source — mi_source_coverage","text":"","code":"if (FALSE) { # \\dontrun{ mi_source_coverage(\"BD_HGNACE2_R3\") mi_source_coverage(\"ghs_smod\") } # }"},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_source_filters.html","id":null,"dir":"Reference","previous_headings":"","what":"Get column values for filtering a source — mi_source_filters","title":"Get column values for filtering a source — mi_source_filters","text":"Fetches possible filtering values given source, year, NUTS level.","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_source_filters.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get column values for filtering a source — mi_source_filters","text":"","code":"mi_source_filters(source_name, year, level, filters = list(), limit = 40)"},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_source_filters.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get column values for filtering a source — mi_source_filters","text":"source_name character string specifying source name (f_resource). year character integer specifying year. level character string specifying NUTS level (\"0\", \"1\", \"2\", \"3\"). filters named list names filter fields values selected values fields. Default empty list. limit integer specifying maximum number results return. Default 2000.","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_source_filters.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get column values for filtering a source — mi_source_filters","text":"tibble fields, labels, possible values filtering.","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_source_filters.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get column values for filtering a source — mi_source_filters","text":"","code":"if (FALSE) { # \\dontrun{ mi_source_filters( source_name = \"DEMO_R_FIND2\", year = 2020, level = \"2\", filters = list(unit = \"YR\") ) } # }"},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_sources.html","id":null,"dir":"Reference","previous_headings":"","what":"Get a list of available data sources — mi_sources","title":"Get a list of available data sources — mi_sources","text":"Get list available data sources","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_sources.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get a list of available data sources — mi_sources","text":"","code":"mi_sources(level, year = NULL, limit = 1000)"},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_sources.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get a list of available data sources — mi_sources","text":"level character string specifying NUTS level (\"0\", \"1\", \"2\", \"3\"). can also always check valid NUTS levels using mi_nuts_levels. year integer length 1, specifying year. Optional. limit integer specifying maximum number results return. Default 2000.","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_sources.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get a list of available data sources — mi_sources","text":"tibble sources following columns: source_name: name data source short_description: short description data source description: description data source","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_sources.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get a list of available data sources — mi_sources","text":"","code":"if (FALSE) { # \\dontrun{ # get up to 10 sources for NUTS level 3 mi_sources(\"3\", limit = 10) # get all sources for NUTS level 3 and year 2020 mi_sources(\"3\", year = 2020) } # }"}] +[{"path":"http://www.ekotov.pro/mapineqr/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2024 mapineqr authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"http://www.ekotov.pro/mapineqr/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Egor Kotov. Author, maintainer.","code":""},{"path":"http://www.ekotov.pro/mapineqr/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Kotov E (2024). mapineqr. Access Mapineq inequality indicators via API. doi:10.32614/CRAN.package.mapineqr, https://github.com/e-kotov/mapineqr. Mills M, Leasure D (2024). “Mapineq Link: Geospatial Dashboard Database.” doi:10.5281/zenodo.13864000.","code":"@Manual{mapineqr, title = {mapineqr. Access Mapineq inequality indicators via API}, author = {Egor Kotov}, year = {2024}, url = {https://github.com/e-kotov/mapineqr}, doi = {10.32614/CRAN.package.mapineqr}, } @Misc{mapineq_link, title = {Mapineq Link: Geospatial Dashboard and Database}, author = {Melinda C Mills and Douglas Leasure}, year = {2024}, month = {October}, publisher = {Mapineq deliverables. Turku: INVEST Research Flagship Centre / University of Turku}, doi = {10.5281/zenodo.13864000}, }"},{"path":"http://www.ekotov.pro/mapineqr/index.html","id":"mapineqr","dir":"","previous_headings":"","what":"Access Mapineq inequality indicators via API","title":"Access Mapineq inequality indicators via API","text":"R package access data https://www.mapineq.org/ API dashboard (product Mapineq proejct)","code":""},{"path":"http://www.ekotov.pro/mapineqr/index.html","id":"mapineqr-1","dir":"","previous_headings":"","what":"mapineqr","title":"Access Mapineq inequality indicators via API","text":"goal mapineqr access data Mapineq.org API dashboard (product Mapineq proejct).","code":""},{"path":"http://www.ekotov.pro/mapineqr/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Access Mapineq inequality indicators via API","text":"can install development version mapineqr GitHub :","code":"if (!require(\"pak\")) install.packages(\"pak\") pak::pak(\"e-kotov/mapineqr\") # load packages used in the examples on this page library(mapineqr) library(dplyr) library(ggplot2) library(eurostat) library(sf) library(biscale)"},{"path":"http://www.ekotov.pro/mapineqr/index.html","id":"basic-example---univariate-data-and-maps","dir":"","previous_headings":"","what":"Basic Example - univariate data and maps","title":"Access Mapineq inequality indicators via API","text":"Get full list available data NUTS 3 level: Select data source source_name column check ’s year NUTS level coverage: Check available filters data source: Choose indicator filter (let burglaries) get data: Map indicator using NUTS2 polygons:","code":"library(mapineqr) available_data <- mi_sources(level = \"3\") head(available_data) # A tibble: 52 × 3 source_name short_description description 1 DEMO_R_D3AREA \"Area by NUTS 3 regio\" Area by NUTS 3 region (ESTAT) 2 PROJ_19RAASFR3 \"Assumptions for fert\" Assumptions for fertility rates by age, type of projection and NUTS… 3 PROJ_19RAASMR3 \"Assumptions for prob\" Assumptions for probability of dying by age, sex, type of projectio… 4 BD_HGNACE2_R3 \"Business demography \" Business demography and high growth enterprise by NACE Rev. 2 and N… 5 BD_SIZE_R3 \"Business demography \" Business demography by size class and NUTS 3 regions (ESTAT) 6 CENS_11DWOB_R3 \"Conventional dwellin\" Conventional dwellings by occupancy status, type of building and NU… 7 CRIM_GEN_REG \"Crimes recorded by t\" Crimes recorded by the police by NUTS 3 regions (ESTAT) 8 DEMO_R_MAGEC3 \"Deaths by age group,\" Deaths by age group, sex and NUTS 3 region (ESTAT) 9 DEMO_R_MWK3_T \"Deaths by week and N\" Deaths by week and NUTS 3 region (ESTAT) 10 DEMO_R_MWK3_TS \"Deaths by week, sex \" Deaths by week, sex and NUTS 3 region (ESTAT) # ℹ 42 more rows # ℹ Use `print(n = ...)` to see more rows mi_source_coverage(\"CRIM_GEN_REG\") # A tibble: 10 × 5 nuts_level year source_name short_description description 1 0 2008 CRIM_GEN_REG Crimes recorded by t Crimes recorded by the police by NUTS 3 regions (ESTAT) 2 0 2009 CRIM_GEN_REG Crimes recorded by t Crimes recorded by the police by NUTS 3 regions (ESTAT) 3 0 2010 CRIM_GEN_REG Crimes recorded by t Crimes recorded by the police by NUTS 3 regions (ESTAT) 4 1 2008 CRIM_GEN_REG Crimes recorded by t Crimes recorded by the police by NUTS 3 regions (ESTAT) 5 1 2009 CRIM_GEN_REG Crimes recorded by t Crimes recorded by the police by NUTS 3 regions (ESTAT) 6 1 2010 CRIM_GEN_REG Crimes recorded by t Crimes recorded by the police by NUTS 3 regions (ESTAT) 7 2 2008 CRIM_GEN_REG Crimes recorded by t Crimes recorded by the police by NUTS 3 regions (ESTAT) 8 2 2009 CRIM_GEN_REG Crimes recorded by t Crimes recorded by the police by NUTS 3 regions (ESTAT) 9 2 2010 CRIM_GEN_REG Crimes recorded by t Crimes recorded by the police by NUTS 3 regions (ESTAT) 10 3 2008 CRIM_GEN_REG Crimes recorded by t Crimes recorded by the police by NUTS 3 regions (ESTAT) mi_source_filters(\"CRIM_GEN_REG\", year = 2010, level = \"2\") # A tibble: 6 × 4 field field_label label value 1 unit Unit of measure Number NR 2 freq Time frequency Annual A 3 iccs International classification of crime for statistical purposes (ICCS) Intentional homicide ICCS0101 4 iccs International classification of crime for statistical purposes (ICCS) Robbery ICCS0401 5 iccs International classification of crime for statistical purposes (ICCS) Burglary of private residential premises ICCS05012 6 iccs International classification of crime for statistical purposes (ICCS) Theft of a motorized land vehicle ICCS050211 x <- mi_data(x_source = \"CRIM_GEN_REG\", year = 2010, level = \"2\", x_filters = list(iccs = \"ICCS05012\")) head(x) # A tibble: 6 × 4 best_year geo geo_name x 1 2008 AT11 Burgenland (A) 223 2 2008 AT12 Niederösterreich 2557 3 2008 AT13 Wien 9319 4 2008 AT21 Kärnten 507 5 2008 AT22 Steiermark 1163 6 2008 AT31 Oberösterreich 988 library(eurostat) library(ggplot2) # load NUTS2 level polygons nuts2 <- eurostat::get_eurostat_geospatial(nuts_level = 2, year = \"2010\", crs = \"4326\") # join data to NUTS2 polygons nuts2_crime <- nuts2 |> left_join(x, by = \"geo\") # plot a map of burglaries map_burglaries <- ggplot(nuts2_crime) + geom_sf(aes(fill = x)) + scale_fill_viridis_c() + labs(title = \"Number of burglaries of private residential premises in 2010\") + theme_minimal() ggsave(\"man/figures/map_burglaries.png\", map_burglaries, width = 8, height = 6, dpi = 200, create.dir = TRUE)"},{"path":"http://www.ekotov.pro/mapineqr/index.html","id":"advanced-example---bivariate-data-and-maps","dir":"","previous_headings":"","what":"Advanced Example - bivariate data and maps","title":"Access Mapineq inequality indicators via API","text":"Select two indicators. Let (1) unemployment rate: (2) life expectancy: Check available filters: Get data two indicators: Plot scratterplot: Add bivariate data NUTS2 polygons create plot:","code":"mi_source_coverage(\"TGS00010\") |> dplyr::arrange(desc(year)) # A tibble: 12 × 5 nuts_level year source_name short_description description 1 2 2022 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) 2 2 2021 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) 3 2 2020 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) 4 2 2019 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) 5 2 2018 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) 6 2 2017 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) 7 2 2016 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) 8 2 2015 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) 9 2 2014 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) 10 2 2013 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) 11 2 2012 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) 12 2 2011 TGS00010 Unemployment rate by Unemployment rate by NUTS 2 regions (ESTAT) mi_source_coverage(\"DEMO_R_MLIFEXP\") |> dplyr::arrange(desc(year)) # A tibble: 96 × 5 nuts_level year source_name short_description description 1 0 2021 DEMO_R_MLIFEXP Life expectancy by a Life expectancy by age, sex and NUTS 2 region (ESTAT) 2 1 2021 DEMO_R_MLIFEXP Life expectancy by a Life expectancy by age, sex and NUTS 2 region (ESTAT) 3 2 2021 DEMO_R_MLIFEXP Life expectancy by a Life expectancy by age, sex and NUTS 2 region (ESTAT) 4 0 2020 DEMO_R_MLIFEXP Life expectancy by a Life expectancy by age, sex and NUTS 2 region (ESTAT) 5 1 2020 DEMO_R_MLIFEXP Life expectancy by a Life expectancy by age, sex and NUTS 2 region (ESTAT) 6 2 2020 DEMO_R_MLIFEXP Life expectancy by a Life expectancy by age, sex and NUTS 2 region (ESTAT) 7 0 2019 DEMO_R_MLIFEXP Life expectancy by a Life expectancy by age, sex and NUTS 2 region (ESTAT) 8 1 2019 DEMO_R_MLIFEXP Life expectancy by a Life expectancy by age, sex and NUTS 2 region (ESTAT) 9 2 2019 DEMO_R_MLIFEXP Life expectancy by a Life expectancy by age, sex and NUTS 2 region (ESTAT) 10 0 2018 DEMO_R_MLIFEXP Life expectancy by a Life expectancy by age, sex and NUTS 2 region (ESTAT) # ℹ 86 more rows # ℹ Use `print(n = ...)` to see more rows mi_source_filters(\"TGS00010\", year = 2018, level = \"2\") # A tibble: 12 × 4 field field_label label value 1 unit Unit of measure Percentage PC 2 isced11 International Standard Classification of Education (ISCED 2011) All ISCED 2011 levels TOTAL 3 isced11 International Standard Classification of Education (ISCED 2011) Less than primary, primary and lower secondary education (levels 0-2) ED0-2 4 isced11 International Standard Classification of Education (ISCED 2011) Upper secondary and post-secondary non-tertiary education (levels 3 and 4) ED3_4 5 isced11 International Standard Classification of Education (ISCED 2011) Tertiary education (levels 5-8) ED5-8 6 isced11 International Standard Classification of Education (ISCED 2011) Unknown UNK 7 isced11 International Standard Classification of Education (ISCED 2011) No response NRP 8 sex Sex Total T 9 sex Sex Males M 10 sex Sex Females F 11 freq Time frequency Annual A 12 age Age class 15 years or over Y_GE15 mi_source_filters(\"DEMO_R_MLIFEXP\", year = 2018, level = \"2\") |> print(n=90) # A tibble: 91 × 4 field field_label label value 1 unit Unit of measure Year YR 2 sex Sex Total T 3 sex Sex Males M 4 sex Sex Females F 5 freq Time frequency Annual A 6 age Age class Less than 1 year Y_LT1 7 age Age class 1 year Y1 8 age Age class 2 years Y2 9 age Age class 3 years Y3 10 age Age class 4 years Y4 11 age Age class 5 years Y5 12 age Age class 6 years Y6 13 age Age class 7 years Y7 14 age Age class 8 years Y8 15 age Age class 9 years Y9 16 age Age class 10 years Y10 17 age Age class 11 years Y11 ... xy_data <- mi_data( year = 2018, level = \"2\", x_source = \"TGS00010\", x_filters = list(isced11 = \"TOTAL\", unit = \"PC\", age = \"Y_GE15\", sex = \"T\", freq = \"A\"), y_source = \"DEMO_R_MLIFEXP\", y_filters = list(unit = \"YR\", age = \"Y_LT1\", sex = \"T\", freq = \"A\") ) edu_v_life_exp_plot <- ggplot(xy_data, aes(x = x, y = y)) + geom_point() + labs(x = \"Percentage of all adults aged 15 years or over with a degree\", y = \"Life expectancy at birth\") + theme_minimal() # ggsave(\"man/figures/edu_v_life_exp_plot.png\", edu_v_life_exp_plot, width = 8, height = 6, units = \"in\", dpi = 300) nuts2 <- eurostat::get_eurostat_geospatial(nuts_level = 2, year = \"2016\", crs = \"4326\") nuts2_edu_v_life_exp <- nuts2 |> left_join(xy_data, by = \"geo\") library(biscale) bidata <- bi_class(nuts2_edu_v_life_exp, x = x, y = y, style = \"quantile\", dim = 3) legend <- bi_legend(pal = \"GrPink\", dim = 3, xlab = \" Higher % with a degree\", ylab = \" Higher life expectancy\", size = 8) map <- ggplot() + geom_sf(data = bidata, mapping = aes(fill = bi_class), color = \"white\", size = 0.1, show.legend = FALSE) + bi_scale_fill(pal = \"GrPink\", dim = 3) + labs( title = \"Education vs Life Expectancy\" ) + bi_theme() png(\"man/figures/edu_v_life_exp_map.png\", width = 8, height = 6, units = \"in\", res = 300) print(map) print(legend, vp = grid::viewport(x = 0.4, y = .75, width = 0.2, height = 0.2, angle = -45)) dev.off()"},{"path":"http://www.ekotov.pro/mapineqr/index.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Access Mapineq inequality indicators via API","text":"cite R package data publications use: Kotov E (2024). mapineqr. Access Mapineq inequality indicators via API. doi:10.32614/CRAN.package.mapineqr https://doi.org/10.32614/CRAN.package.mapineqr, https://github.com/e-kotov/mapineqr. Mills M, Leasure D (2024). “Mapineq Link: Geospatial Dashboard Database.” doi:10.5281/zenodo.13864000 https://doi.org/10.5281/zenodo.13864000. BibTeX:","code":"@Manual{mapineqr, title = {mapineqr. Access Mapineq inequality indicators via API}, author = {Egor Kotov}, year = {2024}, url = {https://github.com/e-kotov/mapineqr}, doi = {10.32614/CRAN.package.mapineqr}, } @Misc{mapineq_link, title = {Mapineq Link: Geospatial Dashboard and Database}, author = {Melinda C Mills and Douglas Leasure}, year = {2024}, month = {October}, publisher = {Mapineq deliverables. Turku: INVEST Research Flagship Centre / University of Turku}, doi = {10.5281/zenodo.13864000}, }"},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Get univariate or bivariate data for a specific source — mi_data","title":"Get univariate or bivariate data for a specific source — mi_data","text":"Fetches univariate bivariate data given source, year, NUTS level, selected filters.","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get univariate or bivariate data for a specific source — mi_data","text":"","code":"mi_data( x_source, y_source = NULL, year, level, x_filters = list(), y_filters = NULL, limit = 2000 )"},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get univariate or bivariate data for a specific source — mi_data","text":"x_source character string specifying source name x variable. y_source (Optional) character string specifying source name y variable. year character integer specifying year. level character string specifying NUTS level (\"0\", \"1\", \"2\", \"3\"). x_filters named list names filter fields x variable values selected values fields. Default empty list. find filters use, use mi_source_filters desired source_name. y_filters (Optional) named list names filter fields y variable values selected values fields. Default NULL. find filters use, use mi_source_filters desired source_name. limit integer specifying maximum number results return. Default 2000.","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get univariate or bivariate data for a specific source — mi_data","text":"tibble following columns: univariate data (y_source provided): best_year: best available year, closest requested year. geo: code NUTS region requested level. geo_name: name NUTS region requested level. x: value univariate variable. bivariate data (y_source provided): best_year: best available year, closest requested year (x y variables). geo: code NUTS region requested level. geo_name: name NUTS region requested level. x: value x variable. y: value y variable.","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get univariate or bivariate data for a specific source — mi_data","text":"","code":"if (FALSE) { # \\dontrun{ # Univariate example mi_data( x_source = \"TGS00010\", year = 2020, level = \"2\", x_filters = list(isced11 = \"TOTAL\", unit = \"PC\", age = \"Y_GE15\", freq = \"A\") ) # Bivariate example mi_data( x_source = \"TGS00010\", y_source = \"DEMO_R_MLIFEXP\", year = 2020, level = \"2\", x_filters = list(isced11 = \"TOTAL\", unit = \"PC\", age = \"Y_GE15\", freq = \"A\"), y_filters = list(unit = \"YR\", age = \"Y_LT1\", freq = \"A\") ) } # }"},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_nuts_levels.html","id":null,"dir":"Reference","previous_headings":"","what":"Get a list of available NUTS levels — mi_nuts_levels","title":"Get a list of available NUTS levels — mi_nuts_levels","text":"Get list available NUTS levels","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_nuts_levels.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get a list of available NUTS levels — mi_nuts_levels","text":"","code":"mi_nuts_levels()"},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_nuts_levels.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get a list of available NUTS levels — mi_nuts_levels","text":"character vector valid NUTS levels accepted functions.","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_nuts_levels.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get a list of available NUTS levels — mi_nuts_levels","text":"","code":"if (FALSE) { # \\dontrun{ mi_nuts_levels() } # }"},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_source_coverage.html","id":null,"dir":"Reference","previous_headings":"","what":"Get NUTS level and Year coverage for a specific source — mi_source_coverage","title":"Get NUTS level and Year coverage for a specific source — mi_source_coverage","text":"Get NUTS level Year coverage specific data source.","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_source_coverage.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get NUTS level and Year coverage for a specific source — mi_source_coverage","text":"","code":"mi_source_coverage(source_name, limit = 1500)"},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_source_coverage.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get NUTS level and Year coverage for a specific source — mi_source_coverage","text":"source_name name data source limit integer specifying maximum number results return. Default 2000.","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_source_coverage.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get NUTS level and Year coverage for a specific source — mi_source_coverage","text":"tibble containing following columns: nuts_level: NUTS level year: year source_name: name data source (mathces source_name requested user) short_description: short description data source description: description data source","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_source_coverage.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get NUTS level and Year coverage for a specific source — mi_source_coverage","text":"","code":"if (FALSE) { # \\dontrun{ mi_source_coverage(\"BD_HGNACE2_R3\") mi_source_coverage(\"ghs_smod\") } # }"},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_source_filters.html","id":null,"dir":"Reference","previous_headings":"","what":"Get column values for filtering a source — mi_source_filters","title":"Get column values for filtering a source — mi_source_filters","text":"Fetches possible filtering values given source, year, NUTS level.","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_source_filters.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get column values for filtering a source — mi_source_filters","text":"","code":"mi_source_filters(source_name, year, level, filters = list(), limit = 40)"},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_source_filters.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get column values for filtering a source — mi_source_filters","text":"source_name character string specifying source name (f_resource). year character integer specifying year. level character string specifying NUTS level (\"0\", \"1\", \"2\", \"3\"). filters named list names filter fields values selected values fields. Default empty list. limit integer specifying maximum number results return. Default 2000.","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_source_filters.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get column values for filtering a source — mi_source_filters","text":"tibble fields, labels, possible values filtering.","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_source_filters.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get column values for filtering a source — mi_source_filters","text":"","code":"if (FALSE) { # \\dontrun{ mi_source_filters( source_name = \"DEMO_R_FIND2\", year = 2020, level = \"2\", filters = list(unit = \"YR\") ) } # }"},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_sources.html","id":null,"dir":"Reference","previous_headings":"","what":"Get a list of available data sources — mi_sources","title":"Get a list of available data sources — mi_sources","text":"Get list available data sources","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_sources.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get a list of available data sources — mi_sources","text":"","code":"mi_sources(level, year = NULL, limit = 1000)"},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_sources.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get a list of available data sources — mi_sources","text":"level character string specifying NUTS level (\"0\", \"1\", \"2\", \"3\"). can also always check valid NUTS levels using mi_nuts_levels. year integer length 1, specifying year. Optional. limit integer specifying maximum number results return. Default 2000.","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_sources.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get a list of available data sources — mi_sources","text":"tibble sources following columns: source_name: name data source short_description: short description data source description: description data source","code":""},{"path":"http://www.ekotov.pro/mapineqr/reference/mi_sources.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get a list of available data sources — mi_sources","text":"","code":"if (FALSE) { # \\dontrun{ # get up to 10 sources for NUTS level 3 mi_sources(\"3\", limit = 10) # get all sources for NUTS level 3 and year 2020 mi_sources(\"3\", year = 2020) } # }"}]