Learning ggmap

Mon, 01 Jan 0001 00:00:00 +0000

This is a document for myself to review ggmap package, and how to get quick start.

ggmap is powerful map plot package in R. Compared with maps package, plots exported from ggmaps are elegant.

Two steps to plot a map: plot a map raster, decorate the base map with your own data.

Step 1: download your base map

You need to know the location you will plot. Define location in two ways showing below:

library(ggmap)
Location1 <- "University of Wisconsin, Milwaukee" #Use your address as your defination
Location2 <- "c(lon = -95.3632715, lat = 29.7632836)" # Use longitude and latitude

Use get_map function to download the raster map in your location. There are 3 map “sources” to obtain a map raster, and each of these sources has multiple “map types”

stamen: “watercolor”, “toner”, “terrain”

googlemap:

osm:(sometimes their servers are unavailable)

myMap <- get_map(location=myLocation, source="stamen", maptype=“watercolor", crop=FALSE)
ggmap(myMap)
##zoom = integer from 3-21
##3 = continent, 10=city, 21=building
##(openstreetmap limit of 18)

Step 2 decorate your map with data

In addition, a developing R package need to be concerned: rMap.

References:

ggmap github

ggmap document

ggmap quick start

[ggmap Introduction](https://dl.dropboxusercontent.com/u/24648660/ggmap useR 2012.pdf)

Learning ggplot2

Mon, 01 Jan 0001 00:00:00 +0000

本课程介绍三种R语言的绘图工具包：plot,qplot,ggplot。三种绘图包的能够和语法均不相同。 plot命令是R语言自带的绘图命令，绘图效果简单，适宜数据分析时绘图。 qplot命令是R语言初级绘图语言包，能够提供符合出版物标准的简单绘图。得到的图形大方美观。

Lesson: Regression Models Introduction

制图：plot(jitter(child,4) ~ parent,galton)

建立回归函数：使用函数lm(linear model)，例如：

regrline <- lm(child~parent, galton)

建立回归函数之后，使用abline(add straight lines to a plot)函数将回归函数在图表中画出，例如

abline(regrline, lwd = 3, col = "red")
#lwd = line width, col = line color

画出直线之后可以使用函数summary查看回归函数的各类参数包括残差，系数，相关系数等等。

qplot

qplot is a basic function in ggplot2 package. It provides some basic plots (e.g. points, smooth, boxplot) for users to learn their database generally.

qplot(hwy, displ, data = mpg)

qplot可调的参数有许多，如下展示


qplot(x, y, data=, color=, shape=, size=, alpha=, geom=, method=, formula=, facets=, xlim=, ylim= xlab=, ylab=, main=, sub=)

x, y, data, color, shape, size这些参数很容易理解。可以使用不同的变量实现变化。

alpha用于调节透明度。0就是全透明，1就是实心。

geom用于调节图表类型，有以下几个选项"point", “smooth”, “boxplot”, “line”, “histogram”, “density”, “bar”, “jitter”.

point表示散点图

smooth做出拟合的曲线图

boxplot做出股价图，此处不使用自定义的最高值，最低值和平均值，而是使用fill定义group，自动计算

qplot(year,averTLO, data = gt_sum, xlab = "Year", ylab = "Land&Ocean Avg Temp", geom = c("boxplot","jitter"),fill=decade)

![boxplot](/image/Land&Ocean Avg Temp vs year_boxplot_jitter.jpeg)

line做出折线图

histogram只针对单变量的柱状分布图，纵轴为count，横轴为该单变量。

density同样只针对单变量，画出该单变量的密度分布图。纵轴为density，横轴为该单变量。

bar即为常规柱状分布图，定义两个变量,利用fill变量可以实现多种变化

qplot(factor(cyl), data=mtcars, geom="bar", fill=factor(gear))

jitter则是在x轴上产生随机变量从而避免图形重叠带来的困扰。例如

p <- ggplot(mpg, aes(displ, hwy))
p + geom_point()
不用jitter散点图的效果

p + geom_point(position = "jitter")
使用上jitter的效果

method和formula这两个选项是针对smooth这个选项而出现的。当smooth选项被调用，默认的拟合方法为loess。还有其他拟合方式允许被调用，如’lm’:线性拟合，‘gam’:generalized additive models,“rlm”: robust regression

For example, to add simple linear regression lines, you'd specify geom="smooth", method="lm", formula=y~x. Changing the formula to y~poly(x,2) would produce a quadratic fit. Note that the formula uses the letters x and y, not the names of the variables.

For method="gam", be sure to load the mgcv package. For method="rml", load the MASS package.

cited from Quick-R

facets这个选项可以利用变量生成不同的分图，该选项的表达方式为：facets=rowvar~colvar，若rowvar或colvar不需要设置变量则用“.”代替。例如facets = .~colvar

利用coord_flip()可以将图表翻转

ggplot(diamonds, aes(color, fill=cut)) + geom_bar() + coord_flip()

需要叠加不同类型的图表是使用c指令，e.g. c("point", "smooth")

qplot(year,averT, data = gt_sum, xlab = "Year", ylab = "Land Avg Temp", geom = c("point","smooth"))

![combine](/image/land avg temp vs year_point_smooth.jpeg)

xlim, ylim, xlab, ylab均容易理解 main,sub用于调节主副标题

ggplot2

ggplot采用图层式绘图方法，可根据自己的意图添加想要的图层，适合绘制复杂的大图。下面是一个展示ggplot绘图语法的例子，其中mpg是ggplot自带的一个关于汽车品牌，性质的数据库。hwy和displ分别是mpg数据库中的字段，表示每加仑汽油行驶的里程数和汽车的排量。

>g<-ggplot(mpg, aes(hwy, displ))
>g+geom_points()+geom_smooth()

How to export a table.

write.table(dataframe, "pathway")

R | Dr. Hui Lin