title: "2-R语言数据结构"
output: html_document
date: "2023-02-02"
矩阵:只允许一种数据类型的二维结构
数据框:每一列只允许一种数据类型
列表:可以装各种数据类型
#重点:数据框
#1.数据框来源
# (1)用代码新建
# (2)由已有数据转换或处理得到
# (3)读取表格文件
# (4)R语言内置数据
#2.新建和读取数据框
df1 <- data.frame(gene = paste0("gene",1:4),
change = rep(c("up","down"),each = 2),
score = c(5,3,-2,-4)) #每一列之间要用,隔开
df1
## gene change score
## 1 gene1 up 5
## 2 gene2 up 3
## 3 gene3 down -2
## 4 gene4 down -4
df2 <- read.csv("gene.csv") #工作目录下
df2
## gene change score
## 1 gene1 up 5
## 2 gene2 up 3
## 3 gene3 down -2
## 4 gene4 down -4
#3.数据框属性
#
dim(df1)
## [1] 4 3
nrow(df1) #行数
## [1] 4
ncol(df1) #列数
## [1] 3
#
rownames(df1) #行名
## [1] "1" "2" "3" "4"
colnames(df1) #列名
## [1] "gene" "change" "score"
#4.数据框取子集
df1$score #删掉score,按tab键试试,$后可用tab切换
## [1] 5 3 -2 -4
df1$gene #取列
## [1] "gene1" "gene2" "gene3" "gene4"
mean(df1$score)
## [1] 0.5
## 按坐标
df1[2,2] #坐行右列
## [1] "up"
df1[2,]
## gene change score
## 2 gene2 up 3
df1[,2]
## [1] "up" "up" "down" "down"
class(df1[2,]) #"data.frame"
## [1] "data.frame"
class(df1[,2]) #"character"
## [1] "character"
df1[c(1,3),1:2] #取第1、3行,取1、2列
## gene change
## 1 gene1 up
## 3 gene3 down
## 按名字
df1[,"gene"]
## [1] "gene1" "gene2" "gene3" "gene4"
df1[,c('gene','change')] #可以同时提多列(把要提出来的列写成向量),$只能提一列
## gene change
## 1 gene1 up
## 2 gene2 up
## 3 gene3 down
## 4 gene4 down
## 按条件(逻辑值)
df1[df1$score>0,] #留TRUE
## gene change score
## 1 gene1 up 5
## 2 gene2 up 3
#思考题,筛选score>0的基因
df1[df1$score > 0, 'gene'] #df1[df1$score > 0, 1]
## [1] "gene1" "gene2"
df1$gene[df1$score > 0]
## [1] "gene1" "gene2"
## 代码思维
#如何取数据框的最后一列?
df1[,3]
## [1] 5 3 -2 -4
df1[,ncol(df1)]
## [1] 5 3 -2 -4
#如何取数据框除了最后一列以外的其他列?
df1[,-ncol(df1)]
## gene change
## 1 gene1 up
## 2 gene2 up
## 3 gene3 down
## 4 gene4 down
#筛选score > 0的基因
df1[df1$score > 0,1]
## [1] "gene1" "gene2"
df1$gene[df1$score > 0]
## [1] "gene1" "gene2"
#5.数据框修改
#改一个格
df1[3,3] <- 5
df1
## gene change score
## 1 gene1 up 5
## 2 gene2 up 3
## 3 gene3 down 5
## 4 gene4 down -4
#改一整列
df1$score <- c(12,23,50,2) #存在的列名<- == 修改
df1
## gene change score
## 1 gene1 up 12
## 2 gene2 up 23
## 3 gene3 down 50
## 4 gene4 down 2
#?
df1$p.value <- c(0.01,0.02,0.07,0.05) #不存在的列名<- == 新增
df1
## gene change score p.value
## 1 gene1 up 12 0.01
## 2 gene2 up 23 0.02
## 3 gene3 down 50 0.07
## 4 gene4 down 2 0.05
#改行名和列名
rownames(df1) <- c("r1","r2","r3","r4") #行列取子集结果为向量,所以修改时也得是向量
#只修改某一行/列的名
colnames(df1)[2] <- "CHANGE"
#6.两个数据框的连接
test1 <- data.frame(name = c('jimmy','nicker','Damon','Sophie'),
blood_type = c("A","B","O","AB"))
test1
## name blood_type
## 1 jimmy A
## 2 nicker B
## 3 Damon O
## 4 Sophie AB
test2 <- data.frame(name = c('Damon','jimmy','nicker','tony'),
group = c("group1","group1","group2","group2"),
vision = c(4.2,4.3,4.9,4.5))
test2
## name group vision
## 1 Damon group1 4.2
## 2 jimmy group1 4.3
## 3 nicker group2 4.9
## 4 tony group2 4.5
test3 <- data.frame(NAME = c('Damon','jimmy','nicker','tony'),
weight = c(140,145,110,138))
test3
## NAME weight
## 1 Damon 140
## 2 jimmy 145
## 3 nicker 110
## 4 tony 138
merge(test1,test2,by="name") #by='共同一列的名字'
## name blood_type group vision
## 1 Damon O group1 4.2
## 2 jimmy A group1 4.3
## 3 nicker B group2 4.9
merge(test1,test3,by.x = "name",by.y = "NAME")
## name blood_type weight
## 1 Damon O 140
## 2 jimmy A 145
## 3 nicker B 110
?merge
##### 矩阵和列表
m <- matrix(1:9, nrow = 3)
colnames(m) <- c("a","b","c") #加列名
m
## a b c
## [1,] 1 4 7
## [2,] 2 5 8
## [3,] 3 6 9
#矩阵取子集,不支持$
m[2,]
## a b c
## 2 5 8
m[,1]
## [1] 1 2 3
m[2,3]
## c
## 8
m[2:3,1:2]
## a b
## [1,] 2 5
## [2,] 3 6
m
## a b c
## [1,] 1 4 7
## [2,] 2 5 8
## [3,] 3 6 9
t(m) #转置
## [,1] [,2] [,3]
## a 1 2 3
## b 4 5 6
## c 7 8 9
as.data.frame(m) #转换成数据框
## a b c
## 1 1 4 7
## 2 2 5 8
## 3 3 6 9
pheatmap::pheatmap(m)
pheatmap::pheatmap(m,cluster_cols = F,cluster_rows = F) #可以在允许范围内修改代码
#列表
l <- list(m1 = matrix(1:9, nrow = 3),
m2 = matrix(2:9, nrow = 2))
l # m1,m2是l列表里的元素名
## $m1
## [,1] [,2] [,3]
## [1,] 1 4 7
## [2,] 2 5 8
## [3,] 3 6 9
##
## $m2
## [,1] [,2] [,3] [,4]
## [1,] 2 4 6 8
## [2,] 3 5 7 9
l[[2]] #两个中括号
## [,1] [,2] [,3] [,4]
## [1,] 2 4 6 8
## [2,] 3 5 7 9
l$m1 #名字取子集
## [,1] [,2] [,3]
## [1,] 1 4 7
## [2,] 2 5 8
## [3,] 3 6 9
# 补充:元素的名字
scores = c(100,59,73,95,45)
names(scores) = c("jimmy","nicker","Damon","Sophie","tony") #有名字的向量,名字为向量属性
scores
## jimmy nicker Damon Sophie tony
## 100 59 73 95 45
scores["jimmy"]
## jimmy
## 100
scores[c("jimmy","nicker")]
## jimmy nicker
## 100 59
names(scores)[scores>60]
## [1] "jimmy" "Damon" "Sophie"
# 删除
rm(l)
rm(df1,df2)
rm(list = ls())
#快捷键 ctrl+l 清空控制台
![unnamed-chunk-1-1.png](https://ask8088-private-1251520898.cos.ap-guangzhou.myqcloud.com/developer-images/article/9199560/a92ta5k982.png?q-sign-algorithm=sha1&q-ak=AKID2uZ1FGBdx1pNgjE3KK4YliPpzyjLZvug&q-sign-time=1675346109;1675353309&q-key-time=1675346109;1675353309&q-header-list=&q-url-param-list=&q-signature=ef9071d2e8fd4981ad5876b3a9856683da7ce3e1)
![unnamed-chunk-1-2.png](https://ask8088-private-1251520898.cos.ap-guangzhou.myqcloud.com/developer-images/article/9199560/i2mdkaw6a1.png?q-sign-algorithm=sha1&q-ak=AKID2uZ1FGBdx1pNgjE3KK4YliPpzyjLZvug&q-sign-time=1675346115;1675353315&q-key-time=1675346115;1675353315&q-header-list=&q-url-param-list=&q-signature=3f6641254eb0d8111e919e410980e8b1ed47bd84)
代码来源于生信技能树
原创声明:本文系作者授权腾讯云开发者社区发表,未经许可,不得转载。
如有侵权,请联系 cloudcommunity@tencent.com 删除。
原创声明:本文系作者授权腾讯云开发者社区发表,未经许可,不得转载。
如有侵权,请联系 cloudcommunity@tencent.com 删除。