--- title: "지도제작 대회" subtitle: "인터랙티브 지도(Mapview)" description: | 인터랙티브 지도를 제작해보자. author: - name: 이광춘 url: https://www.linkedin.com/in/kwangchunlee/ affiliation: 한국 R 사용자회 affiliation-url: https://github.com/bit2r title-block-banner: true format: html: theme: flatly code-fold: true code-overflow: wrap toc: true toc-depth: 3 toc-title: 목차 number-sections: true highlight-style: github self-contained: false default-image-extension: jpg filters: - lightbox lightbox: auto link-citations: true knitr: opts_chunk: message: false warning: false collapse: true comment: "#>" R.options: knitr.graphics.auto_pdf: true editor_options: chunk_output_type: console --- ### 소스코드 [ FelixAnalytix/YouTube ](https://github.com/FelixAnalytix/YouTube) # 패키지 ```{r} #| eval: true if (! require ("tidyverse" )) install.packages ("tidyverse" )if (! require ("BFS" )) install.packages ("BFS" )if (! require ("giscoR" )) install.packages ("giscoR" )if (! require ("mapview" )) install.packages ("mapview" )if (! require ("sf" )) install.packages ("sf" )if (! require ("leafsync" )) install.packages ("leafsync" )if (! require ("leaflet.extras2" )) install.packages ("leaflet.extras2" )library (tidyverse) # data wrangling and viz ecosystem library (BFS) # Search and Download Data from the Swiss Statistical Office library (giscoR) # Access Eurostat Mapping API library (mapview) # Create Interactive Maps easily library (sf) # mapping with Simple Feature library (leaflet) # interactive maps library (leafsync) # plugin for leaflet <- "+proj=longlat +datum=WGS84 +no_defs" ``` # 데이터 ## 지도 ```{r} # switzerland_sf <- gisco_get_nuts( # country = "Switzerland", # nuts_level = 3, # resolution = "01", # cache = TRUE, # update_cache = TRUE) <- sf:: st_read ("data/gisco-services.ec.europa.eu_distribution_v2_nuts_geojson_NUTS_RG_01M_2016_4326_LEVL_3.geojson" )``` ## 스위스 데이터셋 ```{r} # Swiss dataset: https://www.bfs.admin.ch/asset/de/px-x-1502000000_101 <- BFS:: bfs_get_data (number_bfs = "px-x-1502000000_101" , language = "de" , clean_names = TRUE )<- swiss_students %>% pivot_wider (names_from = geschlecht, values_from = lernende) %>% mutate (share_woman = round (Frau/ ` Geschlecht - Total ` * 100 , 1 ))``` ## 지도와 데이터 결합 ```{r} # Preferably using NUTS-3 code if possible <- swiss_students_gender %>% filter (schulkanton != "Schweiz" ) %>% mutate (schulkanton = str_remove (schulkanton, ".*/" ),schulkanton = str_trim (schulkanton),schulkanton = recode (schulkanton, "Berne" = "Bern" , "Grischun" = "Graubünden" , "Wallis" = "Valais" )) %>% left_join (switzerland_sf, by = c ("schulkanton" = "NUTS_NAME" ))``` # 시각화 ## 교육수준 ```{r} <- swiss_student_map %>% filter (jahr == "2001/02" ,!= "Schweiz" ,== "Schweiz" ) %>% select (schulkanton, jahr, bildungsstufe, share_woman, geometry) %>% pivot_wider (names_from = "bildungsstufe" , values_from = "share_woman" ) %>% :: st_as_sf ()%>% mapview (zcol = "Bildungsstufe - Total" , layer.name = "Total education level, % Woman" )``` ## 동기화 ```{r} # Synchronize multiple maps ----------------------------------------------- :: sync (%>% mapview (zcol = "Tertiärstufe" , layer.name = "Tertiary level, % Woman" ),%>% mapview (zcol = "Sekundarstufe II" , layer.name = "Secondary level II, % Woman" ),%>% mapview (zcol = "Obligatorische Schule" , layer.name = "Mandatory school, % Woman" ),%>% mapview (zcol = "Nicht auf Stufen aufteilbare Ausbildungen" , layer.name = "Training that cannot be divided into levels, % Woman" )``` ## 슬라이더 ```{r} # Comparing maps with a slider -------------------------------------------- <- swiss_student_map %>% filter (jahr == "1999/00" ,!= "Schweiz" ,== "Schweiz" ) %>% select (schulkanton, jahr, bildungsstufe, share_woman, geometry) %>% pivot_wider (names_from = "bildungsstufe" , values_from = "share_woman" ) %>% :: st_as_sf ()<- mapview (swiss_student_map_bildungsstufe, zcol = "Bildungsstufe - Total" )<- mapview (swiss_student_map_bildungsstufe_1999, zcol = "Bildungsstufe - Total" )| map2``` # 한국 데이터 ## 지도 ```{r} # korea_sf <- giscoR::gisco_get_nuts( # resolution = "1", # epsg = "4326", # nuts_level = 1, # cache = TRUE, # update_cache = TRUE, # country = "KOR") |> # sf::st_transform(crsLONGLAT) library (sf)library (tidyverse)<- sf:: read_sf ("data/gadm41_KOR_1.json" )<- korea_sf_raw %>% separate (NL_NAME_1, into = c ("시도명" , "한자" ), sep= "( \\ || \\ ()" ) %>% select (시도명, geometry) plot (korea_sf)``` ## 데이터 ```{r} library (krvote)<- krvote:: election_20220309$ 득표율 %>% group_by (시도명) %>% summarise (이재명 = sum (이재명),= sum (윤석열))``` ## 결합 ```{r} <- korea_sf %>% left_join (votes_tbl) %>% mutate (득표마진 = 이재명 - 윤석열)``` # 시각화 ## 대선(이재명) ```{r} library (mapview)<- function (n, alpha = 1 , begin = 0 , end = 1 , direction = 1 ) {<- RColorBrewer:: brewer.pal (11 , "RdBu" )if (direction < 0 ) colors <- rev (colors)colorRampPalette (colors, alpha = alpha)(n)%>% mapview (zcol = "득표마진" , layer.name = "이재명 - 윤석열" , col.regions = palfunc)``` ## 이재명 vs 윤석열 ```{r} library (mapview):: sync (%>% mapview (zcol = "이재명" , layer.name = "이재명 득표수" ),%>% mapview (zcol = "윤석열" , layer.name = "윤석열 득표수" ) ``` ## 대선 비교 ```{r} <- krvote:: election_20121219$ 득표율 %>% group_by (시도명) %>% summarise (박근혜 = sum (박근혜),= sum (문재인))<- korea_sf %>% left_join (vote_2012) %>% mutate (득표마진 = 문재인 - 박근혜)<- mapview (vote_2012_sf, zcol = "득표마진" , layer.name = "이재명 - 윤석열" , col.regions = palfunc)<- mapview (vote_sf, zcol = "득표마진" , layer.name = "문재인 - 박근혜" , col.regions = palfunc)| map_2022``` 