Differences

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--- r:googlevis [2017/06/07 11:43] – [Bar charts] hkimscil
+++ r:googlevis [2017/06/07 17:23] (current) – [Public Parking Places] hkimscil
@@ Line 1: / Line 1: @@
 ====== Worldbank data e.g. ======
-<code>install.packages("googleVis")
+<code>library(googleVis)
+demo(googleVis)</code>
+<code>
+Sys.setlocale(category = "LC_ALL", locale = "us")
+install.packages("googleVis")
 library(googleVis)
 demo(WorldBank)</code>
 {{youtube>nNfT_UBmmu0}}
 <code>
 ## Sys.setlocale("LC_CTYPE", "en_US.UTF-8")  ## comment out if encoding problem occurs
+Sys.setlocale(category = "LC_ALL", locale = "us")
 ## SOURCE: http://lamages.blogspot.co.uk/2011/09/accessing-and-plotting-world-bank-data.html
@@ Line 230: / Line 234: @@
 plot(a)</code>
-<code>library(googleVis)
+====== Public Parking Places ======
-demo(googleVis)</code>
+<code>
+setwd("D:/Users/Hyo/Cs-Kant/CS/Rdata/rloveyou")
+install.packages("ggmap")
+install.packages("stringr")
+library(ggmap)
+library(stringr)
+loc <- read.csv("서울_강동구_공영주차장_위경도.csv")
+loc
+kd <- get_map("Amsa-dong",zoom=13, maptype = "roadmap")
+kor.map <- ggmap(kd)+geom_point(data=loc, aes(x=LON, y=LAT),
+            size=3,alpha=0.7,color="red")
+kor.map + geom_text(data=loc, aes(x = LON, y = LAT+0.001, label=주차장명),size=3)
+ggsave("kd.png",dpi=500)
+# 시립 구립 구분하기
+loc2 <- str_sub(loc$주차장명,start=-2,end=-2)
+loc2
+colors <- c()
+for ( i in 1:length(loc2)) {
+  if (loc2[i] == '구' ) {
+     colors <- c(colors,"red") }
+  else {
+    colors <- c(colors,"blue") }
+ }
+kd <- get_map("Amsa-dong",zoom=13, maptype = "roadmap")
+kor.map <- ggmap(kd)+geom_point(data=loc, aes(x=LON, y=LAT),
+             size=3,alpha=0.7,color=colors)
+kor.map + geom_text(data=loc, aes(x = LON, y = LAT+0.001, label=주차장명),size=3)
+ggsave("kd2.png",dpi=500)
+</code>
+====== Places in Jeju ======
+<code>
+install.packages("googleVis")
+install.packages("ggmap")
+Sys.setlocale("LC_CTYPE", "en_US.UTF-8")
+library(googleVis)
+library(ggmap)
+ft_placelst <- function(place) {
+  temp <- geocode(place)
+  place <- gsub("제주 ","",place)
+  df_lst <- cbind(place,temp)
+  return(df_lst)
+}
+df_placelst <- ft_placelst(readLines("제주여행코스.txt"))
+latlong <- paste(df_placelst$lat,":",df_placelst$lon)
+latlong <- gsub(" ","",latlong)
+df_placelst <- cbind(df_placelst, latlong)
+df_placelst
+placePath <- gvisMap(df_placelst, "latlong" ,"place" ,
+                     options=list(showTip=TRUE, showLine=TRUE,
+                                  enableScrollWheel=TRUE,
+                                  mapType='hybrid',
+                                  useMapTypeControl=TRUE,
+                                  width=800,height=1000))
+plot(placePath)
+</code>
+====== Population by districts ======
+<code>
+library(ggmap)
+library(grid)
+pop <- read.csv("지역별인구현황_2014_4월기준.csv",header=T)
+pop
+lon <- pop$LON
+lat <- pop$LAT
+data <- pop$총인구수
+df <- data.frame(lon,lat,data)
+df
+map1 <- get_map("Jeonju",zoom=7 , maptype='roadmap')
+map1 <- ggmap(map1)
+map1 + geom_point(aes(x=lon,y=lat,colour=data,size=data),data=df)
+ggsave("pop.png",scale=1,width=7,height=4,dpi=500)
+</code>