Differences

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--- r:googlevis [2017/06/07 09:17] – [Places in Jeju] 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 173: / Line 177: @@
 ====== Seoul District Office marking ======
-====== Places in Jeju ======
+====== Google Gauge Chart ======
+<code>library(googleVis)
+CityPopularity
+ex1 <-gvisGauge(CityPopularity, options=list(min=0, max=800,
+                 greenFrom=500, greenTo=800,
+                 yellowFrom=300, yellowTo=500,
+                 redFrom=0, redTo=300, width=400, height=300))
+plot(ex1)
+</code>
+====== Pie charts ======
+<code>library(googleVis)
+CityPopularity
+pie1 <- gvisPieChart(CityPopularity,options=list(width=400, height=300))
+plot(pie1)</code>
+====== Bar charts ======
+<code>library(googleVis)
+fruits=data.frame(month=c("JAN","FEB","MAR"),
+                  apple=c(30,10,20),
+                   orange=c(20,40,30))
+line <- gvisLineChart(fruits)
+plot(line)
+# 양쪽면에 y축 표시하기
+line2 <- gvisLineChart(fruits,"month",c("apple","orange"),
+         option=list(series="[{targetAxisIndex:0},
+                             {targetAxisIndex:1}]",
+         vAxes="[{title:'apple'},{title:'orange'}]" ))
+plot(line2)
+# 선모양 변경하기
+line3 <- gvisLineChart(fruits,xvar="month",yvar=c("apple","orange"),
+         options=list(series="[{color:'blue',targetAxisIndex:0,
+                                linewidth:1,lineDashStyle:[1,10,1,10,1,10]},
+                               {color:'red',targetAxisIndex:1,
+                                linewidth:2,lineDashStyle:[4,1]}]",
+                      vAxes="[{title:'apple'},{title:'orange'}]" ))
+plot(line3)
+</code>
+<code>gbar <- gvisBarChart(fruits)
+plot(gbar)
+</code>
+====== Bubble charts ======
+<code>library(googleVis)
+Fruits
+a <- gvisBubbleChart(Fruits, idvar="Fruit", xvar="Sales", yvar="Expenses",
+                     colorvar="Year", sizevar="Profit",
+                     options=list(height=500,weight=800,
+                                  hAxis='{minValue:75, maxValue:125}'))
+plot(a)</code>
+====== Public Parking Places ======
 <code>
+setwd("D:/Users/Hyo/Cs-Kant/CS/Rdata/rloveyou")
 install.packages("ggmap")
-library(googleVis)
+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$주차장명,start=-2,end=-2)
+loc2
+colors <- c()
+for ( i in 1:length(loc2)) {
+  if (loc2[i] == '구' ) {
+     colors <- c(colors,"red") }
+  else {
+    colors <- c(colors,"blue") }
+ }
+kd <- get_map("Amsa-dong",zoom=13, maptype = "roadmap")
+kor.map <- ggmap(kd)+geom_point(data=loc, aes(x=LON, y=LAT),
+             size=3,alpha=0.7,color=colors)
+kor.map + geom_text(data=loc, aes(x = LON, y = LAT+0.001, label=주차장명),size=3)
+ggsave("kd2.png",dpi=500)
+</code>
+====== Places in Jeju ======
+<code>
+install.packages("googleVis")
+install.packages("ggmap")
+Sys.setlocale("LC_CTYPE", "en_US.UTF-8")
+library(googleVis)
+library(ggmap)
 ft_placelst <- function(place) {
-   temp <- geocode(place) # 이부분이 핵심!! 위도 경도를 임시변수에 담습니다
+  temp <- geocode(place)
-   place <- gsub("Jeju ", "", place)
+  place <- gsub("제주 ","",place)
-   df_lst <- cbind(place, temp) # 여행지이름 위도 경도'로 이루어진 데이터프레임
+  df_lst <- cbind(place,temp)
-   return(df_lst)
+  return(df_lst)
 }
-df_placelst <- ft_placelst(readLines("jeju_places.txt"))
+df_placelst <- ft_placelst(readLines("제주여행코스.txt"))
 latlong <- paste(df_placelst$lat,":",df_placelst$lon)
 latlong <- gsub(" ","",latlong)
 df_placelst <- cbind(df_placelst, latlong)
 df_placelst
@@ Line 200: / Line 301: @@
                                   width=800,height=1000))
 plot(placePath)
 </code>
+====== Population by districts ======
+<code>
+library(ggmap)
+library(grid)
+pop <- read.csv("지역별인구현황_2014_4월기준.csv",header=T)
+pop
+lon <- pop$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>