1.镜像设置
options("repos" = c(CRAN="https://mirrors.tuna.tsinghua.edu.cn/CRAN/"))
options(BioC_mirror="https://mirrors.ustc.edu.cn/bioc/")
镜像设置
2.dplyr的五个基本函数
2.1 mutate(),新增列
mutate(test, new = Sepal.Length * Sepal.Width)
2.1 mutate(),新增列
2.2 select(),按列筛选
(1)按列号筛选
select(test,1)
select(test,c(1,5))
select(test,Sepal.Length)
2.2 select(),按列筛选,(1)按列号筛选
(2)按列名筛选
select(test, Petal.Length, Petal.Width)
vars <- c("Petal.Length", "Petal.Width")
select(test, one_of(vars))
2.2 select(),按列筛选,(2)按列名筛选
2.3 filter()筛选行
filter(test, Species == "setosa")
filter(test, Species == "setosa"&Sepal.Length > 5 )
filter(test, Species %in% c("setosa","versicolor"))
2.3 filter()筛选行
2.4 arrange(),按某1列或某几列对整个表格进行排序
arrange(test, Sepal.Length)#默认从小到大排序
arrange(test, desc(Sepal.Length))#用desc从大到小
2.4 arrange(),按某1列或某几列对整个表格进行排序
2.5 summarise():汇总
summarise(test, mean(Sepal.Length), sd(Sepal.Length))# 计算Sepal.Length的平均值和标准差
# 先按照Species分组,计算每组Sepal.Length的平均值和标准差
group_by(test, Species)
summarise(group_by(test, Species),mean(Sepal.Length), sd(Sepal.Length))
2.5 summarise():汇总
3.dplyr两个实用技能
3.1 管道操作 %>% (cmd/ctr + shift + M)
test %>%
group_by(Species) %>%
summarise(mean(Sepal.Length), sd(Sepal.Length))
3.2 count统计某列的unique值
count(test,Species)
3.dplyr两个实用技能
4.dplyr处理关系数据
options(stringsAsFactors = F)
test1 <- data.frame(x = c('b','e','f','x'),
z = c("A","B","C",'D'),
stringsAsFactors = F)
test1
test2 <- data.frame(x = c('a','b','c','d','e','f'),
y = c(1,2,3,4,5,6),
stringsAsFactors = F)
test2
4.1 內连inner_join,取交集
inner_join(test1, test2, by = "x")
4.2 左连left_join
left_join(test1, test2, by = 'x')
left_join(test2, test1, by = 'x')
4.1和4.2
4.3 全连full_join
full_join( test1, test2, by = 'x')
4.4 半连接:返回能够与y表匹配的x表所有记录semi_join
semi_join(x = test1, y = test2, by = 'x')
4.5 反连接:返回无法与y表匹配的x表的所记录anti_join
anti_join(x = test2, y = test1, by = 'x')
4.3、4.4、4.5
4.6 简单合并
test1 <- data.frame(x = c(1,2,3,4), y = c(10,20,30,40))
test1
test2 <- data.frame(x = c(5,6), y = c(50,60))
test2
test3 <- data.frame(z = c(100,200,300,400))
test3
bind_rows(test1, test2)
bind_cols(test1, test3)
4.6
学习小组Day6笔记--高晨Xmind
以上代码来源于生信星球
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