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twli.R
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twli.R
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library(dplyr)
library(tidyr)
library(stringr)
library(rlang)
library(spdep)
library(rgdal)
library(plm)
library(lmtest)
library(GISTools)
library(raster)
library(maptools)
library(foreign)
library(readr)
library(readxl)
library(writexl)
library(xlsx)
library(stargazer)
library(ggplot2)
library(jsonlite)
library(leaflet)
library(htmlwidgets)
options(warn = -1)
setwd('D:/Users/Torrent/Google 雲端硬碟/stat/R/github/twli_code')
setwd('/media/torrent/Database/Users/torrent/Google 雲端硬碟/stat/R/github/twli_code')
setwd("/media/torrent/Database/User/Google 雲端硬碟/stat/R/github/twli")
setwd("~/Google Drive File Stream/我的雲端硬碟/stat/R/github/twli_code")
result_2009_ty <- read_xlsx("data/result_2009_ty.xlsx")
result_2010_kc <- read_xlsx("data/result_2010_kc.xlsx")
result_2014_kyc <- read_xlsx("data/result_2014_kyc.xlsx")
result_2018_kyc <- read_xlsx("data/result_2018_kyc.xlsx")
li_table <- read_xlsx("data/li_table.xlsx", sheet = "Sheet1", col_types = "text")
x <- read_xlsx("data/li_fongshan.xlsx", col_types = "text")
range <- c("2010", "2014")
year <- "2014"
done <- c("TRUE")
vbox <- c("TRUE")
# liRef 村里合併表格函數原始碼-----
range <- seq(range[1], range[2])
record_year <- colnames(x)[grep("[0-9]{4}", colnames(x))[1]:ncol(x)][nchar(colnames(x)[grep("[0-9]{4}", colnames(x))[1]:ncol(x)]) == 4]
range <- unique(c(range[1], record_year[record_year %in% range], range[length(range)]))
merge_temp <- dplyr::select(x, c(1:7), dplyr::matches(paste(range, collapse = "|")))
merge_year <- intersect(record_year, range)
merge_temp <- merge_temp[rowSums(is.na(merge_temp[, merge_year])) != length(merge_year),]
#不同年度所需各種整併情況
if (year == range[1]) { #檔案年度為資料處理範圍第一年
if (year < merge_year[1]) {
done = FALSE
}
if (done == TRUE) {
chk_row <- data.frame(year = merge_year[1], mode = "vbox", mult = "0", stringsAsFactors = FALSE) %>%
bind_rows(data.frame(year = merge_year[length(merge_year)], mode = "m", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = merge_year[length(merge_year)], mode = "s", mult = "1", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = merge_year[length(merge_year)], mode = "t", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = merge_year[length(merge_year)], mode = "vbox", mult = "0", stringsAsFactors = FALSE))
}
if (done == FALSE) {
chk_row <- data.frame(year = merge_year[1], mode = "m", mult = "0", stringsAsFactors = FALSE) %>%
bind_rows(data.frame(year = merge_year[1], mode = "vbox", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = merge_year[1], mode = "t", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = merge_year[length(merge_year)], mode = "m", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = merge_year[length(merge_year)], mode = "c", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = merge_year[length(merge_year)], mode = "s", mult = "1", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = merge_year[length(merge_year)], mode = "t", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = merge_year[length(merge_year)], mode = "vbox", mult = "0", stringsAsFactors = FALSE))
}
if (length(range) >= 3) {
mid_row <- data.frame(year = c(merge_year[2:(length(merge_year) - 1)]), mode = "m", mult = "0", stringsAsFactors = FALSE) %>%
bind_rows(data.frame(year = c(merge_year[2:(length(merge_year) - 1)]), mode = "c", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = c(merge_year[2:(length(merge_year) - 1)]), mode = "vbox", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = c(merge_year[2:(length(merge_year) - 1)]), mode = "s", mult = "1", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = c(merge_year[2:(length(merge_year) - 1)]), mode = "t", mult = "0", stringsAsFactors = FALSE))
chk_row <- bind_rows(chk_row, mid_row)
}
}
if (year == range[length(range)]) {
if (year > merge_year[length(merge_year)]) {
done = TRUE
}
if (done == TRUE) {
chk_row <- data.frame(year = merge_year[1], mode = "vbox", mult = "0", stringsAsFactors = FALSE) %>%
bind_rows(data.frame(year = merge_year[length(merge_year)], mode = "m", mult = "1", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = merge_year[length(merge_year)], mode = "t", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = merge_year[length(merge_year)], mode = "s", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = merge_year[length(merge_year)], mode = "vbox", mult = "0", stringsAsFactors = FALSE))
}
if (done == FALSE) {
chk_row <- data.frame(year = merge_year[1], mode = "vbox", mult = "0", stringsAsFactors = FALSE) %>%
bind_rows(data.frame(year = merge_year[length(merge_year)], mode = "m", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = merge_year[length(merge_year)], mode = "t", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = merge_year[length(merge_year)], mode = "vbox", mult = "0", stringsAsFactors = FALSE))
}
if (length(merge_year) >= 3) {
mid_row <- data.frame(year = c(merge_year[2:length[merge_year] - 1], mode = "s", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = c(merge_year[2:(length(merge_year) - 1)]), mode = "c", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = c(merge_year[2:(length(merge_year) - 1)]), mode = "vbox", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = c(merge_year[2:(length(merge_year) - 1)]), mode = "t", mult = "0", stringsAsFactors = FALSE))
chk_row <- bind_row(chk_row, mid_row)
}
}
if (year > range[1] & year < range[length(range)]) { #資料年位於處理資料時間範圍的中間
pre_year <- range[range < year] #資料年之前的年度，包括其他資料及x裡面的資料年
if (length(setdiff(range, year)) > 0) { #檢測資料年之前的年度，裡面是否有比x裡面的資料年還前面的
doc_year <- setdiff(pre_year, setdiff(range, year)) #x裡面的資料年之年度
if (done == TRUE) {
chk_row <- data.frame(year = doc_year, mode = "s", mult = "0", stringsAsFactors = FALSE) %>%
bind_rows(data.frame(year = doc_year, mode = "vbox", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = doc_year, mode = "c", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = doc_year, mode = "t", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = year, mode = "m", mult = "1", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = year, mode = "s", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = year, mode = "c", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = year, mode = "t", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = year, mode = "vbox", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = range[length(range)], mode = "m", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = range[length(range)], mode = "t", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = range[length(range)], mode = "vbox", mult = "0", stringsAsFactors = FALSE))
}
if (done == FALSE) {
chk_row <- data.frame(year = doc_year, mode = "s", mult = "0", stringsAsFactors = FALSE) %>%
bind_rows(data.frame(year = doc_year, mode = "t", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = doc_year, mode = "vbox", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = year, mode = "m", mult = "1", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = year, mode = "s", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = year, mode = "t", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = year, mode = "vbox", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = range[length(range)], mode = "m", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = range[length(range)], mode = "t", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = range[length(range)], mode = "vbox", mult = "0", stringsAsFactors = FALSE))
}
}
if (length(setdiff(range, year)) == 0) {
doc_year <- pre_year
if (done == TRUE) {
chk_row <- data.frame(year = doc_year, mode = "vbox", mult = "0", stringsAsFactors = FALSE) %>%
bind_rows(data.frame(year = doc_year, mode = "t", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = doc_year, mode = "c", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = year, mode = "m", mult = "1", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = year, mode = "s", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = year, mode = "c", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = year, mode = "t", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = year, mode = "vbox", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = range[length(range)], mode = "m", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = range[length(range)], mode = "s", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = range[length(range)], mode = "t", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = range[length(range)], mode = "vbox", mult = "0", stringsAsFactors = FALSE))
}
if (done == FALSE) {
chk_row <- data.frame(year = doc_year, mode = "vbox", mult = "0", stringsAsFactors = FALSE) %>%
bind_rows(data.frame(year = doc_year, mode = "t", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = year, mode = "m", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = year, mode = "c", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = year, mode = "t", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = year, mode = "vbox", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = range[length(range)], mode = "m", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = range[length(range)], mode = "t", mult = "0", stringsAsFactors = FALSE)) %>%
bind_rows(data.frame(year = range[length(range)], mode = "vbox", mult = "0", stringsAsFactors = FALSE))
}
}
}
if (vbox == FALSE) {
chk_row <- chk_row %>%
filter(mode != "vbox")
}
merge_list <- list()
for (chk in 1:nrow(chk_row)) {
#chk = 3
mode_chk <- as.character(chk_row$mode[chk])
#done_chk <- as.character(chk_row$done[chk])
if (mode_chk == "vbox") {
merge_chk <- merge_temp %>%
filter(!!sym(paste0("mode_", chk_row$year[chk])) == mode_chk)
} else {
merge_chk <- merge_temp %>%
filter(!!sym(paste0("mode_", chk_row$year[chk])) == mode_chk)
}
if (chk_row$mult[chk] == "1") {
merge_chk <- merge_chk %>%
filter(grepl("\\|", !!sym(chk_row$year[chk])) == TRUE)
}
if(nrow(merge_chk) > 0) {
merge_chk$year <- chk_row$year[chk]
}
merge_list <- bind_rows(merge_list, merge_chk)
}
if (nrow(merge_list) == 0) {
merge_gp <- list()
}
if (nrow(merge_list) > 0) {
merge_gp <- list()
ignore_row <- list()
for (gp in 1:nrow(merge_list)) {
#gp <- 2
if (gp %in% ignore_row) {
} else {
if (length(grep("vbox", merge_list[gp,])) > 0) {
idfy_col <- substr(colnames(merge_list[gp,])[grep("vbox", merge_list[gp,])[1]], regexpr("[0-9]+" ,colnames(merge_list[gp,])[grep("vbox", merge_list[gp,])[1]]),
nchar(colnames(merge_list[gp,])[grep("vbox", merge_list[gp,])[1]]))
gp_list <- unlist(c(strsplit(unlist(merge_list[gp, idfy_col], use.names = FALSE), "|", fixed = TRUE), merge_list$li_id[gp]))
} else {
#從這裡開始，多里合併處理
#gp_cand <- c(unlist(merge_list[gp, merge_list$year[gp]]), unlist(merge_list[gp, "li_id"]))
gp_cand <- paste(c(unlist(merge_list[gp, merge_list$year[gp]]), unlist(merge_list[gp, "li_id"])), collapse = "|")
gp_list <- unlist(strsplit(gp_cand, "|", fixed = TRUE))
complete_row <- gp
mult_lichk <- "1"
while(length(mult_lichk) > 0) {
idfy_row <- grep(gp_cand, unlist(merge_list[, merge_list$year[gp]]))
complete_chk <- gp_list
row_rd <- setdiff(idfy_row, complete_row)
complete_row <- union(idfy_row, complete_row)
#print("1")
#gp_cand <- unique(unlist(c(merge_list[row_rd, merge_list$year[gp]], merge_list[row_rd, "li_id"])))
gp_cand <- c(unlist(merge_list[row_rd, merge_list$year[gp]]), unlist(merge_list[row_rd, "li_id"]))
mult_lichk <- unique(unlist(c(strsplit(unlist(gp_cand), "|", fixed = TRUE))))
mult_lichk <- setdiff(mult_lichk, complete_chk)
gp_list <- c(gp_list, mult_lichk)
gp_cand <- paste(mult_lichk, collapse = "|")
#print("2")
}
ignore_row <- union(ignore_row, complete_row)
ignore_row <- setdiff(ignore_row, gp)
gp_list <- c(sort(setdiff(gp_list, merge_list$li_id[complete_row])), merge_list$li_id[complete_row])
#li_gp <- unlist(c(strsplit(unlist(merge_list[gp, merge_list$year[gp]]), "|", fixed = TRUE), merge_list$li_id[gp]))
#li_gp <- strsplit(gp_list, "|", fixed = TRUE)
}
merge_gp_temp <- data.frame(li_id = gp_list, merge_code = seq(1:length(gp_list)), group = gp)
merge_gp <- rbind(merge_gp, merge_gp_temp)
}
}
}
li_merge_table <- merge_gp
# liSum 村里合併加總原始碼-----
col_range <- c(2:8)
col_name <- colnames(x)[cols]
mg_target <- x %>%
left_join(ref, by = "li_id") %>%
filter(is.na(group) == FALSE)
mg_target <- mg_target %>%
group_by(group) %>%
summarise_at(vars(all_of(col_name)), sum, na.rm = TRUE)
mg_target <- mg_target %>%
left_join(ref[ref$merge_code == "1",], by = "group")
x[match(mg_target$li_id, x$li_id), col_name] <- mg_target[, col_name]
if (finish == TRUE) {
x <- x %>%
filter(!li_id %in% ref$li_id[ref$merge_code != 1])
x <- x %>%
mutate(li_adjust = case_when(li_id %in% ref$li_id[ref$merge_code == 1] ~ 1,
TRUE ~ 0))
}
result_compare <- result_2009_ty %>%
left_join(result_2018_kyc, by = "li_id")
#舊版
for (mg in 1:length(unique(merge_gp$group))) {
#mg = 1
mg_temp <- merge_gp %>%
filter(group == unique(merge_gp$group)[mg])
mg_result <- result_2014_kyc %>%
filter(li_id == mg_temp$li_id[1])
mg_result[, col_range] <- colSums(result_2014_kyc[result_2014_kyc$li_id %in%mg_temp$li_id, col_range], na.rm = TRUE)
result_2014_kyc[result_2014_kyc$li_id == mg_result$li_id,] <- mg_result
result_2014_kyc$li_adjust <- "0"
result_2014_kyc$li_adjust[result_2014_kyc$li_id == mg_result$li_id] <- "1"
result_2014_kyc <- result_2014_kyc %>%
filter(li_id != mg_temp$li_id[-1])
}
# liEqu 村里合併欄位運算原始碼-----
#DPP_2014/(num_voter_2014 - invaild_vote_2014 - Other_2014)
fu <- "DPP_2014 / (num_voter_2014 - invaild_vote_2014 - Other_2014)"
fu <- "(KMT_2010 + Other_2010) / vaild_vote_2010"
equal <- c("KMT_rate_2010")
col_spl <- unlist(strsplit(gsub("\\s", "", equ), "/|-|\\(|\\)|\\*|\\^|\\+"))
col_spl <- col_spl[nchar(col_spl) != 0]
mg_target <- x %>%
dplyr::left_join(ref, by = "li_id") %>%
dplyr::filter(is.na(group) == FALSE)
mg_target <- mg_target %>%
dplyr::group_by(group) %>%
dplyr::summarise_at(vars(all_of(col_spl)), sum, na.rm = TRUE)
mg_target <- mg_target %>%
dplyr::mutate(!!result := !!parse_expr(equ))
mg_target <- mg_target %>%
dplyr::left_join(ref[ref$merge_code == "1",], by = "group")
x[match(mg_target$li_id, x$li_id), c(col_spl, result)] <- mg_target[, c(col_spl, result)]
if (finish == TRUE) {
x <- x %>%
filter(!li_id %in% ref$li_id[ref$merge_code != 1])
x <- x %>%
dplyr::mutate(li_adjust = case_when(li_id %in% ref$li_id[ref$merge_code == 1] ~ 1,
TRUE ~ 0))
}
#### liShp 村里合併shape檔處理-----
for (g_idx in 1:length(unique(ref$group))) {
agg_map <- stats::aggregate(rbind(x[x$li_id %in% ref$li_id[ref$group == g_idx],]))
maintain_li <- x@data[x$li_id == ref$li_id[ref$group == g_idx & ref$merge_code == "1"],]
agg_map <- sp::spChFIDs(agg_map, as.character(x$OBJECTID[x$li_id == ref$li_id[ref$group == g_idx & ref$merge_code == "1"]]))
x <- x[!x$li_id %in% ref$li_id[ref$group == g_idx],]
x <- sp::spChFIDs(x, as.character(x$OBJECTID))
x <- raster::bind(x, agg_map)
x@data[nrow(x@data),] <- maintain_li
}
#舊版
kh_map <- shapefile("data/Kaohsiung/VillageKH_NLSC_1041007.shp")
plot(kh_map)
li_adjusted <- data.frame(li_id = c("6403400-005", "6403400-006", "6403400-008", "6401200-045", "6401200-062"), merge_code = c("1", "2", "2", "1", "2"), group = c("1", "1", "1", "2", "2"))
map_adjusted <- kh_map
for (g_idx in 1:length(unique(li_adjusted$group))) {
agg_map <- aggregate(rbind(map_adjusted[map_adjusted$VILLAGE_ID %in% li_adjusted$li_id[li_adjusted$group == g_idx],]))
maintain_li <- map_adjusted@data[map_adjusted$VILLAGE_ID == li_adjusted$li_id[li_adjusted$group == g_idx & li_adjusted$merge_code == "1"],]
agg_map <- spChFIDs(agg_map, as.character(map_adjusted$OBJECTID[map_adjusted$VILLAGE_ID == li_adjusted$li_id[li_adjusted$group == g_idx & li_adjusted$merge_code == "1"]]))
map_adjusted <- map_adjusted[!map_adjusted$VILLAGE_ID %in% li_adjusted$li_id[li_adjusted$group == g_idx],]
map_adjusted <- spChFIDs(map_adjusted, as.character(map_adjusted$OBJECTID))
map_adjusted <- raster::bind(map_adjusted, agg_map)
map_adjusted@data[nrow(map_adjusted@data),] <- maintain_li
}
shapefile(map_adjusted, "data/map_adjusted/Kaohsiung/kh_map_adjusted_20200217.shp", overwrite = TRUE)
#dbf <- read.dbf("data/map_adjusted/Kaohsiung/kh_map_adjusted_20191022.dbf")
#dbf <- map_adjusted@data
write.dbf(map_adjusted@data, "data/map_adjusted/Kaohsiung/kh_map_adjusted_20200217.dbf")
map_encoding <- shapefile("data/map_adjusted/Kaohsiung/kh_map_adjusted_20200217.shp")
#案例-----
fongshan_2010 <- read.csv("data/fongshan_2010.csv", stringsAsFactors = FALSE)
fongshan_2014 <- read.csv("data/fongshan_2014.csv", stringsAsFactors = FALSE)
li_fongshan <- read_xlsx("data/li_fongshan.xlsx", col_types = c("text"))
fs_ref_2010 <- liRef(li_fongshan, range = c("2010", "2014"), year = "2010")
fs_ref_2014 <- liRef(li_fongshan, range = c("2010", "2014"), year = "2014")
fs_2014_sum <- liSum(fongshan_2014, ref = fs_ref_2014, cols = c(2:9), finish = TRUE)
fs_2010_sum <- liSum(fongshan_2010, ref = fs_ref_2010, cols = c(5:11), finish = TRUE)
fs_2010_rate <- liEqu(fongshan_2010, ref = fs_ref, result = "DDP_rate_2010", equ = c("DPP_2010 / vaild_vote_2010"))
fs_2010_rate <- liEqu(fs_2010_rate, ref = fs_ref, result = "KMT_rate_2010", equ = c("(KMT_2010 + Other_2010) / vaild_vote_2010"), finish = TRUE)
compare_test <- fs_2010_sum %>%
full_join(fs_2014_sum, by = "li_id")
3
fs_map <- shapefile("data/map_adjusted/fongshan/fs_map.shp")
plot(fs_map)
kh_map <- shapefile("data/Kaohsiung/VillageKH_NLSC_1041007.shp")
fs_map <- kh_map[kh_map$TOWN_ID == "6401200",]
fs_map <- shapefile("data/map_adjusted/fongshan/fs_map.shp")
colnames(fs_map@data)[6] <- "li_id"
fs_map_df <- fortify(fs_map, region = "li_id")
fs_map_df$merge[fs_map_df$id == c("6401200-045")] <- "1"
fs_map_df$merge[fs_map_df$id == c("6401200-062")] <- "2"
map <- ggplot(data = fs_map_df, aes(x = long, y = lat, group = group))
map + geom_path(color = "white") +
ggtitle("高雄市鳳山區圖資整併前") +
geom_polygon(aes(fill = merge)) +
coord_fixed(1.3) +
coord_equal() +
scale_fill_discrete(name = NULL,
labels = c("生明里","誠智里","其它")) +
theme(text = element_text(family = "Heiti TC Medium"),
plot.background=element_rect(fill="white", colour=NA),
aspect.ratio = 1) +
xlab(NULL) + ylab(NULL)
ggsave(filename = "fs.png", width = 4,
dpi = 200, plot = last_plot(), device='png'
)
fs_map_adjust <- liShp(fs_map, fs_ref_2014)
fs_map_ad_df <- fortify(fs_map_adjust, region = "li_id")
#fs_map_df <- merge(fs_map_df, fs_ref_2014, by.x = "id", by.y = "li_id", all.x = TRUE)
fs_map_ad_df$merge[fs_map_ad_df$id == c("6401200-045")] <- "1"
fs_map_ad_df$merge[fs_map_ad_df$id == c("6401200-062")] <- "2"
map_ad <- ggplot(data = fs_map_ad_df, aes(x = long, y = lat, group = group))
map_ad + geom_path(color = "white") +
ggtitle("高雄市鳳山區圖資整併後") +
geom_polygon(aes(fill = merge)) +
coord_fixed(1.3) +
coord_equal() +
scale_fill_discrete(name = NULL,
labels = c("生明里","其它")) +
theme(text = element_text(family = "Heiti TC Medium"),
plot.background=element_rect(fill="white", colour=NA),
aspect.ratio = 1) +
xlab(NULL) + ylab(NULL)
ggsave(filename = "fs_a.png", width = 4,
dpi = 200, plot = last_plot(), device='png'
)
with(centroids, annotate(geom="text", x = clong, y = clat, label = centroids$name, size = 2))
+
geom_text(data=centroids, aes(fontface=2 ,centroids$clong, centroids$clat , label = name),
color= "black" ,size=3, check_overlap = T, position=position_jitter(width=3, height=3))
guides(fill = guide_legend(order = 1))
+
shapefile(fs_map, "data/map_adjusted/fongshan/fs_map.shp", overwrite = TRUE)
write.dbf(fs_map@data, "data/map_adjusted/fongshan/fs_map.dbf")
map_encoding <- shapefile("data/map_adjusted/fongshan/fs_map.shp")
####end
for (mg in 1:max(merge_gp$group)) {
mg_temp <- merge_gp %>%
filter(group == unique(merge_gp$group)[mg])
mg_result <- get(merge_obj) %>%
filter(li_id == mg_temp$li_id[1])
#test <- get(merge_obj)[get(merge_obj)$li_id %in%mg_temp$li_id, ]
mg_result[, col_range] <- colSums(get(merge_obj)[get(merge_obj)$li_id %in%mg_temp$li_id, col_range], na.rm = TRUE)
eval(parse(text = paste0(get(merge_obj)[get(merge_obj)$li_id == mg_result$li_id,], "<-", mg_result)))
get(merge_obj)[get(merge_obj)$li_id == mg_result$li_id,] <- mg_result
get(merge_obj)$li_adjust <- "0"
get(merge_obj)$li_adjust[get(merge_obj)$li_id == mg_result$li_id] <- "1"
get(merge_obj) <- get(merge_obj) %>%
filter(li_id != mg_temp$li_id[-1])
}
write_xlsx(result_2009_ty, "result_2009_ty.xlsx")
write_xlsx(result_2010_kc, "result_2010_kc.xlsx")
result_2014_kyc <- result_fm_2014 %>%
filter(substr(li_id, 1, 2) %in% c("64", "66", "68"))
write_xlsx(result_2014_kyc, "result_2014_kyc.xlsx")
write_xlsx(result_2018_kyc, "result_2018_kyc.xlsx")