uribo/Transport_flowmap.R

## Transport_flowmap.R
###################################
# 大都市交通センサス
# 第12回 首都圏 https://www.mlit.go.jp/sogoseisaku/transport/sosei_transport_tk_000007.html
# 線別駅間移動人員,
# 鉄道位置データ: 国土数値情報 鉄道時系列 https://nlftp.mlit.go.jp/ksj/gml/datalist/KsjTmplt-N05-v1_3.html
# 行政区画: 地球地図日本 https://www.gsi.go.jp/kankyochiri/globalmap.html
# 加工・編集者: 瓜生真也 (Shinya Uryu)
#
# mapboxよりアクセストークンを取得してください
###################################
library(flowmapblue)
library(ssrn)
library(sf)
library(dplyr)

d <-
  kuniumi::read_ksj_n05("N05-18_GML/N05-18_Station2.geojson") %>%
  # 現存する駅のみ、新幹線を除く
  filter(timePeriod_End == "9999",
         !timePeriod_Begin %in% c("2016", "2017", "2018"),
         serviceProviderType != "1") %>%
  select(railwayLineName, operationCompany, stationName, geometry) %>%
  mutate(operationCompany = stringr::str_remove_all(operationCompany, "（旧国鉄）")) %>%
  filter(operationCompany != "東日本旅客鉄道" | stationName != "新治") %>%
  filter(operationCompany != "秩父鉄道" | !stationName %in% c("和銅黒谷", "大野原", "秩父", "御花畑",
                                                          "影森", "浦山口", "武州中川", "武州日野",
                                                          "白久", "三峰口")) %>%
  filter(operationCompany != "箱根登山鉄道" | !stationName %in% c("中強羅", "公園下", "公園上", "上強羅", "早雲山")) %>%
  filter(!operationCompany %in% c("御岳登山鉄道", "高尾登山電鉄", "舞浜リゾートライン", "筑波観光鉄道", "真岡鐵道",
                                  "富士急行", "大山観光電鉄", "伊豆箱根鉄道")) %>%
  filter(operationCompany != "東京都" | !stationName %in% c("上野動物園西園", "上野動物園東園")) %>%
  mutate(operationCompany = if_else(operationCompany == "横浜高速鉄道" & stationName %in% c("こどもの国", "恩田", "長津田"),
                                    "東京急行電鉄",
                                    operationCompany),
         stationName = if_else(operationCompany == "相模鉄道" & stationName == "三ツ鏡",
                               "三ツ境",
                               stationName))

# 運営会社で駅を一つに
d <-
  d %>%
  group_by(operationCompany, stationName) %>%
  slice_head(n = 1) %>%
  ungroup() %>%
  select(-railwayLineName)

sf_kanto <-
  sf::st_read("gm-japan/gm-jpn-all_u_2_2/polbnda_jpn.shp") %>%
  sf::st_transform(crs = 4326) %>%
  dplyr::filter(nam %in% c("Tochigi Ken", "Ibaraki Ken",
                           "Saitama Ken", "Kanagawa Ken", "Gunma Ken",
                           "Tokyo To", "Chiba Ken", "Yamanashi Ken")) %>%
  dplyr::filter(adm_code %in% c("08203", "08204", "08205",
                                "08207", "08208", "08210",
                                "08211", "08217", "08219", "08220", "08224",
                                "08227", "08228", "08229", "08230",
                                "08235",
                                "08442", "08443", "08447", "08521", "08542", "08546",
                                "08564",
                                "09203", "09204", "09208", "09364",
                                "10207", "10521", "10522",
                                "11100", "11201", "11202", "11203", "11206",
                                # 除外しても良い？駅があるけどデータがない
                                "11207",
                                "11208", "11209", "11210", "11211", "11212", "11214",
                                "11215", "11216", "11217", "11218", "11219", "11221",
                                "11222", "11223", "11224", "11225", "11227", "11228",
                                "11229", "11230", "11231", "11232", "11233", "11234",
                                "11235", "11237", "11238", "11239", "11240", "11241",
                                "11242", "11243", "11245", "11301",
                                "11324", "11326", "11327", "11341", "11342", "11343", "11346",
                                "11347", "11348", "11349", "11361", "11369", "11381",
                                "11385", "11408", "11442", "11445", "11464", "11465",
                                "12100", "12203", "12204", "12206", "12207", "12208",
                                "12210", "12211", "12212", "12213", "12216", "12217", "12219",
                                "12220", "12221", "12222", "12224", "12225", "12227",
                                "12228", "12229", "12230", "12231", "12232", "12233",
                                "12236", "12237", "12322", "12329", "12342", "12402",
                                "12421", "12423", "12426", "12441",
                                paste0(seq.int(13101, 13360)),
                                "14100", "14130", "14150", "14201", "14203", "14204",
                                "14205", "14206", "14207", "14208", "14210", "14211",
                                "14212", "14213", "14214", "14215", "14216", "14217",
                                "14218", "14301", "14321", "14341", "14342", "14361",
                                "14362", "14363", "14366", "14382", "14382", "14383",
                                "14384", "14401",
                                "19206", "19212"))

sf_target_st_kanto <-
  d %>%
  st_crop(sf_kanto)

# 鉄道駅コード
df_station_code <-
  readxl::read_xlsx("001179689.xlsx",
                    skip = 1,
                    col_names = c("st_code",
                                  "oc_name",
                                  "rw_name",
                                  "st_name",
                                  "oc_code",
                                  "rw_code")) %>%
  mutate(st_name = stringi::stri_trans_general(st_name, "nfkc")) %>%
  mutate(st_name = recode(st_name,
                          `四ッ谷` = "四ツ谷",
                          `巌根` = "巖根",
                          `三ッ沢上町` = "三ツ沢上町",
                          `三ッ沢下町` = "三ツ沢下町",
                          `日本大通り` = "日本大通",
                          `南阿佐ケ谷` = "南阿佐ヶ谷",
                          `西ケ原` = "西ヶ原",
                          `祇園` = "祗園"),
         st_name = if_else(oc_name == "東京地下鉄" & st_name == "市ケ谷",
                           "市ヶ谷",
                           st_name),
         st_name = if_else(oc_name == "東京地下鉄" & st_name == "霞ケ関",
                           "霞ヶ関",
                           st_name),
         oc_name = recode(oc_name,
                          `横浜市交通局` = "横浜市",
                          `東京都交通局` = "東京都"),
         rw_name = stringr::str_remove(rw_name, "（.+）")) %>%
  filter(oc_name != "東日本旅客鉄道" | rw_name != "総武本線" | st_name != "横芝") %>%
  filter(oc_name != "東日本旅客鉄道" | rw_name != "内房線" | !st_name %in% c("青堀", "大貫", "佐貫町", "上総湊", "竹岡", "浜金谷"))
# 線別駅間移動人員
df_passenger <-
  readxl::read_xlsx("001179095.xlsx",
                    col_types = c("text", "text", "numeric", "text", "numeric", "numeric"),
                    skip = 1,
                    col_names = c("rw_code",
                                  "departure_st_code", "departure_status",
                                  "arrive_st_code", "arrive_status",
                                  "volume")) %>%
  mutate(rw_code = stringr::str_pad(rw_code, width = 3, pad = "0"),
         across(ends_with("st_code"), ~stringr::str_pad(.x, width = 5, pad = "0")))

df_passenger_all <-
  df_passenger %>%
  make_passenger_od(df_station_code,
                    depart = departure_st_code,
                    arrive = arrive_st_code,
                    location = st_code,
                    value = volume,
                    .all = FALSE) %>%
  dplyr::left_join(df_station_code %>%
                     select(arrive_st_code = st_code, next_st_name = st_name),
                   by = "arrive_st_code")

sf_target_st_kanto <-
  sf_target_st_kanto %>%
  inner_join(df_station_code,
             by = c("operationCompany" = "oc_name",
                    "stationName" = "st_name"))

df_target_st <-
  sf_target_st_kanto %>%
  mutate(lon = st_coordinates(geometry)[, 1],
         lat = st_coordinates(geometry)[, 2]) %>%
  st_drop_geometry() %>%
  select(id = st_code, name = stationName, lat, lon)

df_passenger_od <-
  df_passenger_all %>%
  select(origin = departure_st_code,
         dest = arrive_st_code,
         count = volume)

mapboxAccessToken <- rstudioapi::askForPassword()
flowmapblue(df_target_st,
            df_passenger_od,
            mapboxAccessToken,
            clustering = TRUE,
            darkMode = FALSE,
            animation = FALSE)
	###################################
	# 大都市交通センサス
	# 第12回首都圏 https://www.mlit.go.jp/sogoseisaku/transport/sosei_transport_tk_000007.html
	# 線別駅間移動人員,
	# 鉄道位置データ: 国土数値情報鉄道時系列 https://nlftp.mlit.go.jp/ksj/gml/datalist/KsjTmplt-N05-v1_3.html
	# 行政区画: 地球地図日本 https://www.gsi.go.jp/kankyochiri/globalmap.html
	# 加工・編集者: 瓜生真也 (Shinya Uryu)
	#
	# mapboxよりアクセストークンを取得してください
	###################################
	library(flowmapblue)
	library(ssrn)
	library(sf)
	library(dplyr)

	d <-
	kuniumi::read_ksj_n05("N05-18_GML/N05-18_Station2.geojson") %>%
	# 現存する駅のみ、新幹線を除く
	filter(timePeriod_End == "9999",
	!timePeriod_Begin %in% c("2016", "2017", "2018"),
	serviceProviderType != "1") %>%
	select(railwayLineName, operationCompany, stationName, geometry) %>%
	mutate(operationCompany = stringr::str_remove_all(operationCompany, "（旧国鉄）")) %>%
	filter(operationCompany != "東日本旅客鉄道" \| stationName != "新治") %>%
	filter(operationCompany != "秩父鉄道" \| !stationName %in% c("和銅黒谷", "大野原", "秩父", "御花畑",
	"影森", "浦山口", "武州中川", "武州日野",
	"白久", "三峰口")) %>%
	filter(operationCompany != "箱根登山鉄道" \| !stationName %in% c("中強羅", "公園下", "公園上", "上強羅", "早雲山")) %>%
	filter(!operationCompany %in% c("御岳登山鉄道", "高尾登山電鉄", "舞浜リゾートライン", "筑波観光鉄道", "真岡鐵道",
	"富士急行", "大山観光電鉄", "伊豆箱根鉄道")) %>%
	filter(operationCompany != "東京都" \| !stationName %in% c("上野動物園西園", "上野動物園東園")) %>%
	mutate(operationCompany = if_else(operationCompany == "横浜高速鉄道" & stationName %in% c("こどもの国", "恩田", "長津田"),
	"東京急行電鉄",
	operationCompany),
	stationName = if_else(operationCompany == "相模鉄道" & stationName == "三ツ鏡",
	"三ツ境",
	stationName))

	# 運営会社で駅を一つに
	d <-
	d %>%
	group_by(operationCompany, stationName) %>%
	slice_head(n = 1) %>%
	ungroup() %>%
	select(-railwayLineName)

	sf_kanto <-
	sf::st_read("gm-japan/gm-jpn-all_u_2_2/polbnda_jpn.shp") %>%
	sf::st_transform(crs = 4326) %>%
	dplyr::filter(nam %in% c("Tochigi Ken", "Ibaraki Ken",
	"Saitama Ken", "Kanagawa Ken", "Gunma Ken",
	"Tokyo To", "Chiba Ken", "Yamanashi Ken")) %>%
	dplyr::filter(adm_code %in% c("08203", "08204", "08205",
	"08207", "08208", "08210",
	"08211", "08217", "08219", "08220", "08224",
	"08227", "08228", "08229", "08230",
	"08235",
	"08442", "08443", "08447", "08521", "08542", "08546",
	"08564",
	"09203", "09204", "09208", "09364",
	"10207", "10521", "10522",
	"11100", "11201", "11202", "11203", "11206",
	# 除外しても良い？駅があるけどデータがない
	"11207",
	"11208", "11209", "11210", "11211", "11212", "11214",
	"11215", "11216", "11217", "11218", "11219", "11221",
	"11222", "11223", "11224", "11225", "11227", "11228",
	"11229", "11230", "11231", "11232", "11233", "11234",
	"11235", "11237", "11238", "11239", "11240", "11241",
	"11242", "11243", "11245", "11301",
	"11324", "11326", "11327", "11341", "11342", "11343", "11346",
	"11347", "11348", "11349", "11361", "11369", "11381",
	"11385", "11408", "11442", "11445", "11464", "11465",
	"12100", "12203", "12204", "12206", "12207", "12208",
	"12210", "12211", "12212", "12213", "12216", "12217", "12219",
	"12220", "12221", "12222", "12224", "12225", "12227",
	"12228", "12229", "12230", "12231", "12232", "12233",
	"12236", "12237", "12322", "12329", "12342", "12402",
	"12421", "12423", "12426", "12441",
	paste0(seq.int(13101, 13360)),
	"14100", "14130", "14150", "14201", "14203", "14204",
	"14205", "14206", "14207", "14208", "14210", "14211",
	"14212", "14213", "14214", "14215", "14216", "14217",
	"14218", "14301", "14321", "14341", "14342", "14361",
	"14362", "14363", "14366", "14382", "14382", "14383",
	"14384", "14401",
	"19206", "19212"))

	sf_target_st_kanto <-
	d %>%
	st_crop(sf_kanto)

	# 鉄道駅コード
	df_station_code <-
	readxl::read_xlsx("001179689.xlsx",
	skip = 1,
	col_names = c("st_code",
	"oc_name",
	"rw_name",
	"st_name",
	"oc_code",
	"rw_code")) %>%
	mutate(st_name = stringi::stri_trans_general(st_name, "nfkc")) %>%
	mutate(st_name = recode(st_name,
	`四ッ谷` = "四ツ谷",
	`巌根` = "巖根",
	`三ッ沢上町` = "三ツ沢上町",
	`三ッ沢下町` = "三ツ沢下町",
	`日本大通り` = "日本大通",
	`南阿佐ケ谷` = "南阿佐ヶ谷",
	`西ケ原` = "西ヶ原",
	`祇園` = "祗園"),
	st_name = if_else(oc_name == "東京地下鉄" & st_name == "市ケ谷",
	"市ヶ谷",
	st_name),
	st_name = if_else(oc_name == "東京地下鉄" & st_name == "霞ケ関",
	"霞ヶ関",
	st_name),
	oc_name = recode(oc_name,
	`横浜市交通局` = "横浜市",
	`東京都交通局` = "東京都"),
	rw_name = stringr::str_remove(rw_name, "（.+）")) %>%
	filter(oc_name != "東日本旅客鉄道" \| rw_name != "総武本線" \| st_name != "横芝") %>%
	filter(oc_name != "東日本旅客鉄道" \| rw_name != "内房線" \| !st_name %in% c("青堀", "大貫", "佐貫町", "上総湊", "竹岡", "浜金谷"))
	# 線別駅間移動人員
	df_passenger <-
	readxl::read_xlsx("001179095.xlsx",
	col_types = c("text", "text", "numeric", "text", "numeric", "numeric"),
	skip = 1,
	col_names = c("rw_code",
	"departure_st_code", "departure_status",
	"arrive_st_code", "arrive_status",
	"volume")) %>%
	mutate(rw_code = stringr::str_pad(rw_code, width = 3, pad = "0"),
	across(ends_with("st_code"), ~stringr::str_pad(.x, width = 5, pad = "0")))

	df_passenger_all <-
	df_passenger %>%
	make_passenger_od(df_station_code,
	depart = departure_st_code,
	arrive = arrive_st_code,
	location = st_code,
	value = volume,
	.all = FALSE) %>%
	dplyr::left_join(df_station_code %>%
	select(arrive_st_code = st_code, next_st_name = st_name),
	by = "arrive_st_code")

	sf_target_st_kanto <-
	sf_target_st_kanto %>%
	inner_join(df_station_code,
	by = c("operationCompany" = "oc_name",
	"stationName" = "st_name"))

	df_target_st <-
	sf_target_st_kanto %>%
	mutate(lon = st_coordinates(geometry)[, 1],
	lat = st_coordinates(geometry)[, 2]) %>%
	st_drop_geometry() %>%
	select(id = st_code, name = stationName, lat, lon)

	df_passenger_od <-
	df_passenger_all %>%
	select(origin = departure_st_code,
	dest = arrive_st_code,
	count = volume)

	mapboxAccessToken <- rstudioapi::askForPassword()
	flowmapblue(df_target_st,
	df_passenger_od,
	mapboxAccessToken,
	clustering = TRUE,
	darkMode = FALSE,
	animation = FALSE)