# 数据产生
# rnorm(n, mean = 0, sd = 1) 正态分布的随机数（r 代表随机，可以替换成dnorm, pnorm, qnorm 作不同计算。r= random = 随机， d= density = 密度， p= probability = 概率 ， q =quantile = 分位）
# runif(n, min = 0, max = 1) 平均分布的随机数
# rep(1,5) 把1重复5次
# scale(1:5) 标准化数据
> a <- c(rnorm(5), rnorm(5,1), runif(5), runif(5,-1,1), 1:5, rep(0,5), c(2,10,11,13,4), scale(1:5)[1:5])
> a
[1] -0.41253556 0.12192929 -0.47635888 -0.97171653 1.09162243 1.87789657
[7] -0.11717937 2.92953522 1.33836620 -0.03269026 0.87540920 0.13005744
[13] 0.11900686 0.76663940 0.28407356 -0.91251181 0.17997973 0.50452258
[19] 0.25961316 -0.58052230 1.00000000 2.00000000 3.00000000 4.00000000
[25] 5.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
[31] 2.00000000 10.00000000 11.00000000 13.00000000 4.00000000 -1.26491106
[37] -0.63245553 0.00000000 0.63245553 1.26491106
> a <- matrix(a, ncol=5, byrow=T)
> a
[,1] [,2] [,3] [,4] [,5]
[1,] -0.4125356 0.1219293 -0.4763589 -0.9717165 1.09162243
[2,] 1.8778966 -0.1171794 2.9295352 1.3383662 -0.03269026
[3,] 0.8754092 0.1300574 0.1190069 0.7666394 0.28407356
[4,] -0.9125118 0.1799797 0.5045226 0.2596132 -0.58052230
[5,] 1.0000000 2.0000000 3.0000000 4.0000000 5.00000000
[6,] 0.0000000 0.0000000 0.0000000 0.0000000 0.00000000
[7,] 2.0000000 10.0000000 11.0000000 13.0000000 4.00000000
[8,] -1.2649111 -0.6324555 0.0000000 0.6324555 1.26491106
# 求行的加和
> rowSums(a)
[1] -0.6470593 5.9959284 2.1751865 -0.5489186 15.0000000 0.0000000 40.0000000
[8] 0.0000000
# 去除全部为0的行
> a <- a[rowSums(abs(a))!=0,]
> a
[,1] [,2] [,3] [,4] [,5]
[1,] -0.4125356 0.1219293 -0.4763589 -0.9717165 1.09162243
[2,] 1.8778966 -0.1171794 2.9295352 1.3383662 -0.03269026
[3,] 0.8754092 0.1300574 0.1190069 0.7666394 0.28407356
[4,] -0.9125118 0.1799797 0.5045226 0.2596132 -0.58052230
[5,] 1.0000000 2.0000000 3.0000000 4.0000000 5.00000000
[6,] 2.0000000 10.0000000 11.0000000 13.0000000 4.00000000
[7,] -1.2649111 -0.6324555 0.0000000 0.6324555 1.26491106
# 矩阵运算，R默认针对整个数据进行常见运算
# 所有值都乘以2
> a * 2
[,1] [,2] [,3] [,4] [,5]
[1,] -0.8250711 0.2438586 -0.9527178 -1.9434331 2.18324487
[2,] 3.7557931 -0.2343587 5.8590704 2.6767324 -0.06538051
[3,] 1.7508184 0.2601149 0.2380137 1.5332788 0.56814712
[4,] -1.8250236 0.3599595 1.0090452 0.5192263 -1.16104460
[5,] 2.0000000 4.0000000 6.0000000 8.0000000 10.00000000
[6,] 4.0000000 20.0000000 22.0000000 26.0000000 8.00000000
[7,] -2.5298221 -1.2649111 0.0000000 1.2649111 2.52982213
# 所有值取绝对值，再取对数 （取对数前一般加一个数避免对0或负值取对数）
> log2(abs(a)+1)
[,1] [,2] [,3] [,4] [,5]
[1,] 0.4982872 0.1659818 0.5620435 0.9794522 1.0646224
[2,] 1.5250147 0.1598608 1.9743587 1.2255009 0.0464076
[3,] 0.9072054 0.1763961 0.1622189 0.8210076 0.3607278
[4,] 0.9354687 0.2387621 0.5893058 0.3329807 0.6604014
[5,] 1.0000000 1.5849625 2.0000000 2.3219281 2.5849625
[6,] 1.5849625 3.4594316 3.5849625 3.8073549 2.3219281
[7,] 1.1794544 0.7070437 0.0000000 0.7070437 1.1794544
# 取出最大值、最小值、行数、列数
> max(a)
[1] 13
> min(a)
[1] -1.264911
> nrow(a)
[1] 7
> ncol(a)
[1] 5
# 增加一列或一行
# cbind: column bind
> cbind(a, 1:7)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.4125356 0.1219293 -0.4763589 -0.9717165 1.09162243 1
[2,] 1.8778966 -0.1171794 2.9295352 1.3383662 -0.03269026 2
[3,] 0.8754092 0