跟小洁老师学习R语言的第三天

k1=rnorm(12);k1
k2=rep(c("a","b","c","d"),each=3);k2
plot(k1)
boxplot(k1~k2)

df1 <- data.frame(gene   = paste0("gene",1:4),
                  change  = rep(c("up","down"),each = 2),
                  score   = c(5,3,-2,-4))

df2 <- read.csv("gene.csv")

iris
volcano
letters
LETTERS
#前十三位letters[1:13]
whitch(letters==M)

#查看行列
dim(df1)
#查看列
nrow(df1)
#查看行
ncol(df1)
#查看列的名字
rownames(df1)
#查看行的名字
colnames(df1)

df1$gene 
mean(df1$score)
# 按坐标
df1[2,2]
df1[2,]
df1[,2]
df1[c(1,3),1:2]#中括号里的逗号，表示维度的分割
# 按名字
df1[,"gene"]
df1[，c('gene','change')]
# 按条件（逻辑值）
df1[df1$score>0,]

#取数据框的最后一列？
df1[,3]
df1[,ncol(df1)]
#取数据框除了最后一列以外的其他列？
df1[,-ncol(df1)]
#筛选score > 0的基因
df1[df1$score > 0,1]#只需要第一列
df1$gene[df1$score > 0]

#改一个格
df1[3,3] <- 5
#改一整列
df1$score <- c(12,23,50,2)     
#增加一列
df1$p.value <- c(0.01,0.02,0.07,0.05) 
#改行名和列名
rownames(df1) <- c("r1","r2","r3","r4")
#只修改某一行/列的名
colnames(df1)[2] <- "CHANGE"

test1 <- data.frame(name = c('jimmy','nicker','Damon','Sophie'), 
                    blood_type = c("A","B","O","AB"))
test1
test2 <- data.frame(name = c('Damon','jimmy','nicker','tony'),
                    group = c("group1","group1","group2","group2"),
                    vision = c(4.2,4.3,4.9,4.5))
test2

test3 <- data.frame(NAME = c('Damon','jimmy','nicker','tony'),
                    weight = c(140,145,110,138))
test3
merge(test1,test2,by="name")
merge(test1,test3,by.x = "name",by.y = "NAME")

m <- matrix(1:9, nrow = 3)
colnames(m) <- c("a","b","c") #加列名
pheatmap::pheatmap(m)
#形成一一对应的关系
pheatmap::pheatmap(m,cluster_rows = F,cluster_cols = F)
m[2,]
m[,1]
m[2,3]
m[2:3,1:2]
#矩阵的转换
t(m)
#转换为数据框，没有赋值就没有变
as.data.frame(m)
#列表
l <- list(m1 = matrix(1:9, nrow = 3),
          m2 = matrix(2:9, nrow = 2)
                                                        
l[[2]]
l$m1

#删除一个
rm(l)
#删除多个
rm(df1,df2)
#删除全部
rm(list = ls())
#清空控制台
ctrl+l
#也可以选择environment右上角的小扫帚 

scores = c(100,59,73,95,45)
names(scores) = c("jimmy","nicker","Damon","Sophie","tony")
scores
scores["jimmy"]
scores[c("jimmy","nicker")]
names(scores)[scores>60]