R Notebook

df<-read.csv("https://raw.githubusercontent.com/tuyenhavan/Statistics/Dataset/My_data.csv",sep=",")

head(df)

##   FID Field1       lat      lon ser
## 1   0      1 -37.74922 175.6729   T
## 2   1      2 -43.26288 170.3655   H
## 3   2      3 -37.67690 175.4695   P
## 4   3      4 -37.27856 175.4390   B
## 5   4      5 -37.25098 175.5982   C
## 6   5      6 -37.64233 175.3597   T

library(ggmap)

## Warning: package 'ggmap' was built under R version 3.2.5

## Loading required package: ggplot2

## Warning: package 'ggplot2' was built under R version 3.2.5

library(ggplot2)

library(RgoogleMaps)

## Warning: package 'RgoogleMaps' was built under R version 3.2.5

library(sp)

## Warning: package 'sp' was built under R version 3.2.5

# Create a spatial point data frame from ` a data frame`

coordinates(df)<-~lon+lat

proj4string(df)<- CRS("+proj=longlat +datum=WGS84")

# amke plot larger

par(mar=rep(2,4))

plot(df)

# Combine online maps with spatial point data frame

points<-data.frame(df)

nz<-get_map(location = "NZ",zoom = 5, maptype = "terrain")

## Map from URL : http://maps.googleapis.com/maps/api/staticmap?center=NZ&zoom=5&size=640x640&scale=2&maptype=terrain&language=en-EN&sensor=false

## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=NZ&sensor=false

ggmap(nz, base_layer = ggplot(data=points)) + geom_point(aes(x=lon,y=lat,color=ser)) + facet_grid(~ser) + ggtitle("Distribution of Ser") + xlab("Longitute") + ylab("Latitude") + theme(plot.title = element_text(hjust=0.5))