R基礎--快速探索數據（《R可視化》）
---恢復內容開始---
安裝軟件包並加載
> install.packages(‘gcookbook‘)
>install.packages(‘ggplot2‘)
> library(ggplot2)
或者：install.packages(‘ggplot2‘,‘gcokbook‘)
> library(gcookbook)
設置工作路徑：
> setwd("d:/data")
> getwd()
[1] "d:/data"
讀取文件
> data <- read.csv(‘dadtafile.csv‘)
> data
X1 X3.8.1941 X1.1.2007
1 2 1/24/1972 1/1/2007
2 3 6/1/1932 1/1/2007
3 4 5/17/1947 1/1/2007
4 5 3/10/1943 1/1/2007
5 6 1/8/1940 1/1/2007
6 7 8/5/1947 1/1/2007
7 8 4/14/2005 1/1/2007
8 9 6/23/1961 1/2/2007
9 10 1/10/1949 1/2/2007
> data <- read.csv(‘dadtafile.csv‘,header=FALSE)
> data
V1 V2 V3
1 1 3/8/1941 1/1/2007
2 2 1/24/1972 1/1/2007
3 3 6/1/1932 1/1/2007
4 4 5/17/1947 1/1/2007
5 5 3/10/1943 1/1/2007
6 6 1/8/1940 1/1/2007
7 7 8/5/1947 1/1/2007
8 8 4/14/2005 1/1/2007
9 9 6/23/1961 1/2/2007
10 10 1/10/1949 1/2/2007
> head(data)
V1 V2 V3
1 1 3/8/1941 1/1/2007
2 2 1/24/1972 1/1/2007
3 3 6/1/1932 1/1/2007
4 4 5/17/1947 1/1/2007
5 5 3/10/1943 1/1/2007
6 6 1/8/1940 1/1/2007
> names(data) <- c(‘Column1‘,‘Column1‘,‘Column1‘)
> data
Column1 Column1 Column1
1 1 3/8/1941 1/1/2007
2 2 1/24/1972 1/1/2007
3 3 6/1/1932 1/1/2007
4 4 5/17/1947 1/1/2007
5 5 3/10/1943 1/1/2007
6 6 1/8/1940 1/1/2007
7 7 8/5/1947 1/1/2007
8 8 4/14/2005 1/1/2007
9 9 6/23/1961 1/2/2007
10 10 1/10/1949 1/2/2007
>
sep參數設置分隔符號：
> data <- read.csv(‘datafile.csv‘,sep=‘\t‘)
#制表符 使用 \t
讀入的字符型比如：china會被識別為因子，所以stringsAsFactors=FALSE
即：> data <- read.csv(‘dadtafile.csv‘)
> data$Sex <- factor(data$Sex)
#轉換為因子
> str(data)
‘data.frame‘: 10 obs. of 3 variables:
$ Column1: int 1 2 3 4 5 6 7 8 9 10
$ Column1: Factor w/ 10 levels "1/10/1949","1/24/1972",..: 5 2 8 7 4 3 10 6 9 1
$ Column1: Factor w/ 2 levels "1/1/2007","1/2/2007": 1 1 1 1 1 1 1 1 2 2
---恢復內容結束---
---恢復內容開始---
安裝軟件包並加載
> install.packages(‘gcookbook‘)
>install.packages(‘ggplot2‘)
> library(ggplot2)
或者：install.packages(‘ggplot2‘,‘gcokbook‘)
> library(gcookbook)
設置工作路徑：
> setwd("d:/data")
> getwd()
[1] "d:/data"
讀取文件
> data <- read.csv(‘dadtafile.csv‘)
> data
X1 X3.8.1941 X1.1.2007
1 2 1/24/1972 1/1/2007
2 3 6/1/1932 1/1/2007
3 4 5/17/1947 1/1/2007
4 5 3/10/1943 1/1/2007
5 6 1/8/1940 1/1/2007
6 7 8/5/1947 1/1/2007
7 8 4/14/2005 1/1/2007
8 9 6/23/1961 1/2/2007
9 10 1/10/1949 1/2/2007
> data <- read.csv(‘dadtafile.csv‘,header=FALSE)
> data
V1 V2 V3
1 1 3/8/1941 1/1/2007
2 2 1/24/1972 1/1/2007
3 3 6/1/1932 1/1/2007
4 4 5/17/1947 1/1/2007
5 5 3/10/1943 1/1/2007
6 6 1/8/1940 1/1/2007
7 7 8/5/1947 1/1/2007
8 8 4/14/2005 1/1/2007
9 9 6/23/1961 1/2/2007
10 10 1/10/1949 1/2/2007
> head(data)
V1 V2 V3
1 1 3/8/1941 1/1/2007
2 2 1/24/1972 1/1/2007
3 3 6/1/1932 1/1/2007
4 4 5/17/1947 1/1/2007
5 5 3/10/1943 1/1/2007
6 6 1/8/1940 1/1/2007
> names(data) <- c(‘Column1‘,‘Column1‘,‘Column1‘)
> data
Column1 Column1 Column1
1 1 3/8/1941 1/1/2007
2 2 1/24/1972 1/1/2007
3 3 6/1/1932 1/1/2007
4 4 5/17/1947 1/1/2007
5 5 3/10/1943 1/1/2007
6 6 1/8/1940 1/1/2007
7 7 8/5/1947 1/1/2007
8 8 4/14/2005 1/1/2007
9 9 6/23/1961 1/2/2007
10 10 1/10/1949 1/2/2007
>
sep參數設置分隔符號：
> data <- read.csv(‘datafile.csv‘,sep=‘\t‘)
#制表符 使用 \t
讀入的字符型比如：china會被識別為因子，所以stringsAsFactors=FALSE
即：> data <- read.csv(‘dadtafile.csv‘)
> data$Sex <- factor(data$Sex)
#轉換為因子
> str(data)
‘data.frame‘: 10 obs. of 3 variables:
$ Column1: int 1 2 3 4 5 6 7 8 9 10
$ Column1: Factor w/ 10 levels "1/10/1949","1/24/1972",..: 5 2 8 7 4 3 10 6 9 1
$ Column1: Factor w/ 2 levels "1/1/2007","1/2/2007": 1 1 1 1 1 1 1 1 2 2
read.table()
read.xlsx()
install.packages(xlsx)
library(xlsx)
library()若不成功，則參考：https://wenku.baidu.com/view/1bc6610ece2f0066f433229f.html
下載java:https://www.java.com/en/download/manual.jsp
> head(mtcars)
mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
>
> plot(wt,mpg)
Error in plot(wt, mpg) : object ‘wt‘ not found
> attach(mtcars)
> plot(wt,mpg)
> detach(mtcars)
>#par函數可實現一頁多圖，顏色。粗細等...
ggplot2中：
> library(ggplot2)
> attach(mtcars)
> qplot(wt,mpg)
> detach(mtcars)
等價於：
> qplot(wt,mpg,data=mtcars)
等價於：
> ggplot(mtcars,aes(x=wt,y=mpg))+geom_point()
> ?plot
查看幫助
Usage
plot(x, y, ...)
Arguments
x
the coordinates of points in the plot. Alternatively, a single plotting structure, function or any R object with a plot method can be provided.
y
the y coordinates of points in the plot, optional if x is an appropriate structure.
...
Arguments to be passed to methods, such as graphical parameters (see par). Many methods will accept the following arguments:
type
what type of plot should be drawn. Possible types are
"p" for points,
"l" for lines,
"b" for both,
"c" for the lines part alone of "b",
"o" for both ‘overplotted’,
"h" for ‘histogram’ like (or ‘high-density’) vertical lines,
"s" for stair steps,
"S" for other steps, see ‘Details’ below,
"n" for no plotting.
All other types give a warning or an error; using, e.g., type = "punkte" being equivalent to type = "p" for S compatibility. Note that some methods, e.g. plot.factor, do not accept this.
main
an overall title for the plot: see title.
sub
a sub title for the plot: see title.
xlab
a title for the x axis: see title.
ylab
a title for the y axis: see title.
asp
the y/x aspect ratio, see plot.window.
> plot(pressure$temperature,pressure$pressure)
> plot(pressure$temperature,pressure$pressure,type="l")
>
> points(pressure$temperature,pressure$pressure)
>
> lines(pressure$temperature,pressure$pressure/2,col="red")
> points(pressure$temperature,pressure$pressure/2,col="red")
>
> qplot(pressure$temperature,pressure$pressure,geom="line")
> qplot(temperature,pressure,data=pressure,geom=c("line","point"))
等價於：
> ggplot(pressure,aes(x=temperature,y=pressure))+geom_line()+geom_point()
> data <- mtcars
> table(cyl)
cyl
4 6 8
11 7 14
#計算頻數
> head(mtcars)
mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
> barplot(BOD$demand,names.arg=BOD$Time)
> barplot(table(cyl))
> qplot(BOD$Time,BOD$demand,geom="bar",stat="identity")
> qplot(factor(BOD$Time),BOD$demand,geom="bar",stat="identity")
繪制不了！
Error: stat_count() must not be used with a y aesthetic.
In addition: Warning message:
`stat` is deprecated
> qplot(mtcars$cyl)
> qplot(factor(mtcars$cyl))
> ggplot(BOD,aes(Time,demand))+geom_bar(stat = ‘identity‘)
> ggplot(BOD,aes(x=factor(Time),y=demand))+geom_bar(stat="identity")
>
https://www.cnblogs.com/lizhilei-123/p/6722116.html
ggplot2之快速作圖qplot()----顏色。透明度，形狀
頻數條形圖：
> library(ggplot2)
> ggplot(mtcars,aes(x=factor(cyl)))+geom_bar()
等價：
> qplot(factor(cyl),data=mtcars)
條形圖與直方圖看起來相似，但是卻是不一樣的，條形圖的x軸是一個確定的數值，而直方圖是一個區間。
> hist(mtcars$mpg,breaks=10)
#breaks=10 組距為10
> qplot(mpg,data = mtcars,binwidth=4)
或者
> ggplot(mtcars,aes(x=mpg))+geom_histogram(binwidth = 4)
>binwidth參數是調節橫坐標的區間，你可以任意調節你認為合適的區間。
plot(ToothGrowth$supp, ToothGrowth$len)
boxplot(len~supp,data = ToothGrowth)
qplot(supp,len,data=ToothGrowth,geom = ‘boxplot‘)
ggplot(ToothGrowth,aes(supp,len))+geom_boxplot()
r code execution error？？？
重裝吧。。。。。。。。。。
系統C盤空間容量不夠。
R基礎--快速探索數據（《R可視化》）