Project Django Data,Map upload

wjddyd66 · Jul 5, 2019 · a90f557 · a90f557
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diff --git a/Django/Data/Map.R b/Django/Data/Map.R
@@ -0,0 +1,48 @@
+library(ggplot2)
+library(ggmap)
+library(xlsx)
+library(readxl)
+library(dplyr)
+
+#데이터 불러오기
+location <- read_excel("location.xlsx",na="NA")
+count <- read_excel("count.xlsx",na="NA")
+#Column 명 변경
+colnames(location) <- c('number','name','x','y')
+#Column 숫자로 변경
+location$number <- as.numeric(location$number)
+location$x <- as.numeric(location$x)
+location$y <- as.numeric(location$y)
+
+#Count Data에 x,y좌표 추가
+for(i in 1:length(count$number)){
+  for(j in 1:length(location$x)){
+    if(count$number[i] == location$number[j]){
+      count$x[i] <- location$x[j]
+      count$y[i] <- location$y[j]
+    }
+  }
+}
+
+#Map을 위한 Data 저장 
+write.xlsx(people,file="map.xlsx")
+
+#MapData 불러오기
+data<-read_excel("map.xlsx",na="NA")
+
+#MapData 상위 100개, 하위100개 나누기
+many <- data[1:100,]
+min <- data[length(data$number)-936:length(data$number),]
+
+#GoogleMap Key 등록
+register_google(key='개인API')
+
+#GoogleMap 을 활용한 Map그리기
+center <- c(mean(data$x),mean(data$y))
+seoul <- get_map(center, zoom=11, maptype='roadmap')
+
+#상위 100개 지도에 그리기
+ggmap(seoul) + geom_point(data=many,aes(x=x,y=y),size=2.5,alpha=0.8,col='red')
+
+#하위 100개 지도에 그리기
+ggmap(seoul) + geom_point(data=min,aes(x=x,y=y),size=2.5,alpha=0.8,col='blue')
diff --git a/Django/Data/count.xlsx b/Django/Data/count.xlsx
diff --git a/Django/Data/location.xlsx b/Django/Data/location.xlsx
diff --git a/Django/Data/map.xlsx b/Django/Data/map.xlsx
diff --git a/Django/Data/park.xlsx b/Django/Data/park.xlsx
diff --git a/Django/Data/people.xlsx b/Django/Data/people.xlsx
diff --git a/Django/Data/pop.xlsx b/Django/Data/pop.xlsx
diff --git a/Django/Data/river.xlsx b/Django/Data/river.xlsx
diff --git a/Django/Data/road.xlsx b/Django/Data/road.xlsx
diff --git a/Django/Data/univ.xlsx b/Django/Data/univ.xlsx
diff --git a/Django/Map.R b/Django/Map.R
@@ -0,0 +1,48 @@
+library(ggplot2)
+library(ggmap)
+library(xlsx)
+library(readxl)
+library(dplyr)
+
+#데이터 불러오기
+location <- read_excel("location.xlsx",na="NA")
+count <- read_excel("count.xlsx",na="NA")
+#Column 명 변경
+colnames(location) <- c('number','name','x','y')
+#Column 숫자로 변경
+location$number <- as.numeric(location$number)
+location$x <- as.numeric(location$x)
+location$y <- as.numeric(location$y)
+
+#Count Data에 x,y좌표 추가
+for(i in 1:length(count$number)){
+  for(j in 1:length(location$x)){
+    if(count$number[i] == location$number[j]){
+      count$x[i] <- location$x[j]
+      count$y[i] <- location$y[j]
+    }
+  }
+}
+
+#Map을 위한 Data 저장 
+write.xlsx(people,file="map.xlsx")
+
+#MapData 불러오기
+data<-read_excel("map.xlsx",na="NA")
+
+#MapData 상위 100개, 하위100개 나누기
+many <- data[1:100,]
+min <- data[length(data$number)-936:length(data$number),]
+
+#GoogleMap Key 등록
+register_google(key='개인API')
+
+#GoogleMap 을 활용한 Map그리기
+center <- c(mean(data$x),mean(data$y))
+seoul <- get_map(center, zoom=11, maptype='roadmap')
+
+#상위 100개 지도에 그리기
+ggmap(seoul) + geom_point(data=many,aes(x=x,y=y),size=2.5,alpha=0.8,col='red')
+
+#하위 100개 지도에 그리기
+ggmap(seoul) + geom_point(data=min,aes(x=x,y=y),size=2.5,alpha=0.8,col='blue')