R语言练习代码

1x <- c(1:10)
2
3x <- c(v1 = 1:4,v2 = 10:14)
4
5install.packages()
6
7install.packages("xlsx")
8
9install.packages("rJava")
10
11install.packages("xlsxjars")
12
13install.packages("vcd")
14
15.libPaths()
16
17install.packages(c("AER","ca"))
18
19library()
20
21library(xlsx)
22
23library(rJava)
24
25print()
26
27require(vcd)
28
29require(xlsx)
30
31installed.packages()
32
33installed.packages()[,1]
34
35Rpack <- installed.packages()[,1]
36save(Rpack,file = "Rpack.Rdata")
37for (i in Rpack) install.packages(i)
38
39help.xlsx()
40help.start()
41
42x <- read.csv("碧彩测试数据1.07",header = TRUE)
43
44y <- readClipboard()
45
46read.table("clipboard",sep = ",",header = TRUE)
47
48read.table("clipboard",sep = "\t",header = TRUE)
49
50install.packages("arules")
51
52data(Groceries)
53
54Groceries
55
56a <- c(100,rep(10,4))
57mean(a)
58b <- c(1000,rep(50,9),rep(5,5))
59sum(b)
60
61A <- c(1,2,5,8,9)
62jicha <- max(A) - min(A)
63jicha
64
65fangcha <- function(x){return(sum((x-mean(x))^2)/length(x))}
66fangcha
67fangcha(A)
68
69install.packages("moments")
70library("moments")
71
72data1
73
74x <- read.csv("C:\\Users\\QDM\\Desktop\\销售业绩.csv",header = T)
75x
76
77y <- read.table("C:\\Users\\QDM\\Desktop\\销售业绩.txt",header = T)
78y
79
80z <- read.table("clipboard",header = T,sep = "\t")
81z
82
831+3
84
85x <- c(1,3,8,4,7,5,6,1)
86png(file = "barchart.png")
87barplot(x)
88dev.off()
89
90x <- read.table("clipboard",header = T,sep = "\t")
91x
92
93x <- read.table("clipboard",header = T)
94x
95
96barplot(apply(x,1,mean))
97
98barplot(apply(x,2,median))
99
100pie(apply(x,2,mean))
101
102barplot(height = 1:10)
103
104data <- cbind(a = 1:4, b = 1:4)
105barplot(data)
106
107data <- cbind(a = 1:4, b = 1:4)
108barplot(data, beside = T)
109
110barplot(1:5, width = 5:1)
111
112barplot(1:3, space = c(0.1, 0.2, 0.3))
113
114par(mfrow = c(1, 2))
115height <- c(1:3)
116names(height) <- c("A", "B", "C")
117barplot(height)
118
119data <- cbind("A" = 1:4, "B" = 1:4)
120barplot(data)
121
122par(mfrow = c(1, 2))
123height <- c(1:3)
124names(height) <- c("A", "B", "C")
125barplot(height, names.arg = c("A1", "A2", "A3"))
126
127data <- cbind("A" = 1:4, "B" = 1:4)
128barplot(data, names.arg = c("D", "E"))
129
130data <- cbind(a = 1:4, b = 1:4)
131rownames(data) <- c("A", "B", "C", "D")
132barplot(data, legend.text = TRUE)
133
134data <- cbind(a = 1:4, b = 1:4)
135rownames(data) <- c("A", "B", "C", "D")
136barplot(data, legend.text = c("E", "F", "G", "H"))
137
138par(mfrow = c(1, 2))
139data <- cbind(a = 1:4, b = 1:4)
140barplot(data, main = "beside = F")
141barplot(data, beside = T, main = "beside = T")
142
143par(mfrow = c(1, 2))
144barplot(1:4, main = "horiz = F")
145barplot(1:4, main = "horiz = T", horiz =T)
146
147barplot(1:4, col = "green")
148
149barplot(1:4, col = rainbow(4))
150
151barplot(1:4, col = rainbow(4), border = NA, main = "border = NA")
152
153par(mfrow = c(1, 3))
154barplot(rep(1,4), density = 1, main = "density = 1")
155barplot(rep(1,4), density = 2, main = "density = 2")
156barplot(rep(1,4), density = 3, main = "density = 3")
157
158par(mfrow = c(1, 3))
159barplot(rep(1,4), density = 2, angle = 45,  main  = "angle = 45")
160barplot(rep(1,4), density = 2, angle = 90,  main  = "angle = 90")
161barplot(rep(1,4), density = 2, angle = 180, main  = "angle = 180") 
162
163par(mfrow = c(1, 2))
164data <- cbind(a = 1:4, b = 1:4)
165barplot(data, axes = F, main = "axes = F")
166barplot(data, axes = T, main = "axes = T")
167
168par(mfrow = c(1, 2))
169data <- cbind(a = 1:4, b = 1:4)
170barplot(data, axisnames = F, main = "axisnames = F")
171barplot(data, axisnames = T, main = "axisnames = T")
172
173par(mfrow = c(1, 3))
174data <- cbind(a = 1:4, b = 1:4)
175barplot(data, offset = 0, main = "offset = 0")
176barplot(data, offset = 1, main = "offset = 1")
177barplot(data, offset = 2, main = "offset = 2")
178
179barplot(1:4, col = rainbow(4), border = NA, main = "border = NA")
180
181barplot(height = 1:7)
182barplot(height = 1:7,beside = T, main = "2020年5月份业绩")
183barplot(height = 1:7,beside = T, main = "2020年5月份业绩",col = rainbow(7))
184barplot(height = 1:7,beside = T, main = "2020年5月份业绩",col = rainbow(7),border = NA)
185barplot(height = 1:7,beside = T, main = "2020年5月份业绩",col = rainbow(7),border = NA)
186
187QDM <- read.table("clipboard",header = T)
188QDM
189
190QDM <- c(100,200,300,400,500,600)
191depatment <- c("电商","水产","水果","蔬菜","肉类","综合")
192barplot(QDM,names.arg = depatment)
193barplot(QDM,names.arg = depatment,col = "green")
194barplot(QDM,names.arg = depatment,col = "red")
195barplot(QDM,names.arg = depatment,col = "blue")
196barplot(QDM,names.arg = depatment,col = "black")
197barplot(QDM,names.arg = depatment,col = "pink")
198barplot(QDM,names.arg = depatment,beside = T, main = "2020年5月份各部门业绩",col = rainbow(7))
199barplot(QDM,names.arg = depatment,beside = T, main = "2020年5月份各部门业绩",col = rainbow(7),border = NA)
200
201data <- c(60,70,80,90,100)
202barplot(data)
203
204
205data1 <- c(60,70,80,90,100)
206bumen <- c("水产","水果","蔬菜","猪肉","综合")
207barplot(data1,names.arg = bumen)
208
209barplot(y,names.arg = x,border = NA,xlab = "部门",ylab = "销售额",main = "2020年5月份各部门总销售额",col = rainbow(4))
210barplot(y,names.arg = x,border = "blue",xlab = "部门",ylab = "销售额",main = "2020年5月份各部门总销售额",col = rainbow(4))
211
212x <- c(1020,1640,1340,1610,1942)
213x
214
215y <- c("水产","水果","蔬菜","猪肉","综合")
216y
217
218plot(x,names.arg = y)
219barplot(x,names.arg = y,border = NA)
220barplot(x,names.arg = y,border = NA,col = rainbow(5))
221plot(x,names.arg = y,type = "b")
222plot(x,names.arg = y,type = "b",col = "red")
223plot(x,names.arg = y,type = "b",col = "green")
224plot(x,names.arg = y,type = "b",col = "DarkTurquoise")
225
226
227n <- 6
228pie(x,n)
229pie(x,y,border = NA)
230pie(x,y,border = NA,col = rainbow(7))
231pie(x,y,col = rainbow(7))
232piecolors <- rainbow(n)
233piecolors
234pie(x,y,border = "gray",col = rainbow(7))
235a <- c(100,150,130,168,111)
236pie(a,y)
237
238
239x <- c(1,2,3,4,5,6,7)
240y <- c("周一","周二","周三","周四","周五","周六","周日")
241barplot(x,names.arg = y)
242barplot(x,names.arg = y,col = rainbow(7))
243barplot(x,names.arg = y,col = rainbow(7),border = NA)
244
245
246pie(x,y)
247pie(x,y,col = brewer.pal(7,"Set1"))
248
249
250write.table(x,file = "result.txt", sep = "\t", quote = FALSE)
251
252x <- read.table("clipboard",header = T,sep = "\t")
253x
254
255y <- read.csv("出入库.csv",header = TRUE)
256y
257
258
259ls("package:graphics")
260
261x <- c(1:4)
262y <- c(4:6)
263arrows(x,y)
264
265
266stars(x)
267box(x)
268demo(graphics)
269
270help(package = "graphics")
271example("heatmap")
272example("barplot")
273example("pie")
274
275
276pie(rep(1, n), labels = "", col = rainbow(n), border = NA,
277    pie+     main = "pie(*, labels=\"\", col=rainbow(n), border=NA,..")
278
279pie(c(Sky = 78, "Sunny side of pyramid" = 17, "Shady side of pyramid" = 5),
280         pie+     init.angle = 315, col = c("deepskyblue", "yellow", "yellow3"), border = FALSE)
281
282pie> pie(c(Sky = 78, "Sunny side of pyramid" = 17, "Shady side of pyramid" = 5),
283         pie+     init.angle = 315, col = c("deepskyblue", "yellow", "yellow3"), border = FALSE)
284
285example("boxplot")
286
287women
288plot(women)
289barplot(women$height)
290barplot(women$height,women$weight)
291plot("fit")
292methods(plot)
293methods(print)
294par()
295barplot(height = 1:3,col = c("red","green","blue"))
296barplot(height = 1:3,col = c("red","green","blue"),border = NA)
297
298
299
300plot(women$height,women$weight)
301
302fit <- lm(height ~ weight,data = women)
303fit
304summary(fit)
305
306install.packages("ggplot2")
307?ggplot2
308?barplot
309install.packages("caret")
310library("caret")
311library(caret)
312data()
313cars
314women
315GermanCredit
316GermanCredit
317GermanCredit
318
319?pie
320x <- c("蔬菜","水果","水产","猪肉","综合")
321x
322y <- c(5,4,3,2,1)
323y
324pie(y,labels = names(x))
325pie(y,labels = names(x),col = rainbow(5))
326pie(y,labels = names(x),col = rainbow(5),border = NA)
327pie(y,labels = names(x),col = rainbow(5),border = NA,edges = 200)
328pie(y,labels = names(x),col = rainbow(5),border = NA,edges = 10)
329pie(y,labels = names(x),col = rainbow(5),border = NA,radius = 1)
330pie(y,labels = names(x),col = rainbow(5),border = NULL,radius = 1)
331pie(y,labels = names(x),col = rainbow(5),border = "white",radius = 1)
332pie(y,labels = names(x),col = rainbow(5),border = NULL,radius = 1,main = "滕玉龙")
333pie(y,labels = names(x),col = rainbow(5),border = NULL,radius = 1, angle = 45)
334pie(y,labels = names(x),col = rainbow(5),border = NULL,radius = 1, clockwise = TRUE)
335pie(y,labels = names(x),col = rainbow(5),border = NA,radius = 1, clockwise = TRUE)
336pie(y,labels = names(x),col = rainbow(5),border = NA,radius = 1, clockwise = TRUE,main = "滕玉龙")
337example(pie)
338pie(y,names(x) <- c("蔬菜","水果","水产","猪肉","综合") ,col = rainbow(5),border = NA,radius = 1, clockwise = TRUE,main = "7月份各部门销售占比")
339
340library("ggplot2")
341qplot(Wind,Temp,data = airquality)
342qplot(Wind,Temp,data = airquality,color = Month)
343qplot(Wind,Temp,data = airquality,color = I("blue"))
344qplot(Wind,Temp,data = airquality,shape = Month)
345qplot(Wind,Temp,data = airquality,size = Month)
346qplot(Wind,Temp,data = airquality,size = I(15))
347qplot(Wind,Temp,data = airquality,size = I(10),color = I("red"),xlab = "风速",ylab = "气温",main = "气温与风速的关系")
348qplot(Wind,Temp,data = airquality,size = I(10),color = I("red"),xlab = "风速",ylab = "气温",main = "气温与风速的关系",fill = Month)
349qplot(Wind,data = airquality,fill = Month)
350qplot(Wind,data = airquality,geom = "density")
351qplot(Wind,data = airquality,geom = "density",color = Month)
352qplot(Wind,data = airquality,geom = "dotplot",color = I("green"))
353
354
355df = data.frame(x=1:10, 
356                y=seq(1, 20, 2), 
357                z=seq(1000, 100, -100), 
358                c=paste("color", seq(1, 10, 1)))
359df
360
361
362install.packages("ggplot2") # 安装包
363install.packages("RColorBrewer")
364library(ggplot2) # 加载包
365library(RColorBrewer)
366
367ggplot(df, aes(x=x, y=y)) +
368  geom_bar(stat="identity")
369
370
371ggplot(df, aes(x=x, y=y, fill=c)) + 
372  geom_bar(stat="identity") +
373  labs(x="x axis", y="y axis", fill="legend")
374
375ggplot(df, aes(x=x, y=y, fill=x)) +
376  geom_bar(stat="identity") +
377  labs(x="x axis", y="y axis", fill="legend")
378
379
380ggplot(df, aes(x=x, y=y, fill=z)) +
381  geom_bar(stat="identity") +
382  labs(x="x axis", y="y axis", fill="legend")
383
384
385colors <- colorRampPalette(c("red", "orange"))(10)
386colors
387# [1] "#FF0000" "#FF1200" "#FF2400" "#FF3700" "#FF4900" "#FF5B00" "#FF6E00" "#FF8000" "#FF9200" "#FFA500"
388
389ggplot(df, aes(x=x, y=y)) +
390  geom_bar(stat="identity", fill=colors[rank(10:1)]) +
391  labs(x="x axis", y="y axis", fill="legend")
392
393
394ggplot(df, aes(x=x, y=y)) +
395  geom_bar(stat="identity", fill=brewer.pal(10, "Set3")) +
396  labs(x="x axis", y="y axis", fill="legend")
397
398?data.frame
399
400?barplot
401
402goods <- c("豆芽","茄子","淮山","番茄","芋头","土豆","萝卜","马蹄","莴笋","红薯")
403goods
404
405amount
406
407barplot(height = 1:10,col = rainbow(10),border = NA,names.arg = goods,main = "各种农产品的产量（单位：万吨）\n\nMade By 滕玉龙",sub = "左手Python，右手R语言",ylab = "产量（万吨）",xlab = "农产品名称")
408
409amount <- c(100, 130, 169, 220, 286, 372, 484, 629, 818, 1063)
410amount
411
412barplot(height = amount,col = rainbow(10),border = NA,names.arg = goods,main = "各种农产品的产量（单位：万吨）\n\nMade By 滕玉龙",sub = "左手Python，右手R语言",ylab = "产量（万吨）",xlab = "农产品名称")
413
414
415
416grade <- c("大一", "大二", "大三", "大四")
417
418amount <- c(15, 38, 123, 35)
419
420barplot(height = amount,col = rainbow(4),border = NA,names.arg = grade,main = "各年级发生的频次",sub = "哈佛在等我呢~",ylab = "频次",xlab = "年级")