如何替换R数据框中的完整列?
要替换R数据框中的完整列,我们可以使用delta运算符将原始列设置为新值。例如,如果我们有一个名为df的数据框,其中包含一列x,其中x的列具有500个来自正态分布的值,则可以用df $x <-rnorm(500,5 )。
例1
考虑以下数据帧-
x1<−rpois(20,2)输出结果x2<−rpois(20,2)
x3<−rpois(20,3)
df1<−data.frame(x1,x2,x3)
df1
x1 x2 x31 1 3 1
2 0 3 1
3 1 4 3
4 4 3 2
5 0 4 1
6 2 3 6
7 2 2 4
8 4 1 2
9 0 4 5
10 1 1 4
11 3 3 1
12 1 3 3
13 1 1 10
14 2 1 3
15 2 3 3
16 1 1 3
17 2 4 8
18 1 3 2
19 1 3 0
20 1 1 0
用具有lambda 2的泊松分布替换x3-
示例
df1$x3<−rpois(20,2)输出结果df1
x1 x2 x31 1 3 1
2 0 3 2
3 1 4 0
4 4 3 1
5 0 4 3
6 2 3 2
7 2 2 2
8 4 1 3
9 0 4 2
10 1 1 3
11 3 3 1
12 1 3 2
13 1 1 3
14 2 1 0
15 2 3 0
16 1 1 1
17 2 4 2
18 1 3 3
19 1 3 4
20 1 1 1
例2
y1<−rnorm(20,1,0.05)输出结果y2<−rnorm(20,1,0.75)
y3<−rnorm(20,1,0.05)
y4<−rnorm(20,1,0.05)
df2<−data.frame(y1,y2,y3,y4)
df2
y1 y2 y3 y41 1.0141018 0.71738148 0.9420311 1.0009205
2 1.0258060 1.03202326 1.0183309 1.0953612
3 0.9743657 1.58046651 1.0517233 1.0596325
4 1.0199483 1.08089945 0.9873335 0.9910522
5 1.0740019 2.13191506 1.0805077 1.0352464
6 1.0504327 1.55207108 1.0105741 0.9503119
7 0.9656107 1.51496959 1.0856465 1.0721738
8 1.0314142 −0.62997358 0.9007254 0.9555474
9 0.9688579 2.05252761 0.9920891 0.9693772
10 0.9811555 1.58630688 0.9550110 0.9611265
11 0.9594506 1.49768858 0.9792084 0.9442541
12 0.9891804 0.50237995 0.8821927 1.0816134
13 1.0939416 0.16319086 1.0682660 0.9552987
14 1.0437989 2.06159460 1.0034599 0.9708994
15 0.9660916 1.21363074 0.9780202 0.9961647
16 1.0634504 0.82467522 1.0184935 1.0586482
17 0.9907623 1.06935013 1.0507246 0.9516461
18 1.0336085 2.07268738 0.9972536 0.9815386
19 1.0366192 2.20583375 1.0393763 0.9332535
20 1.0861114 0.02966648 1.0502028 0.9452250
用均值1和标准差0.05-的正态分布替换y2
示例
df2$y2<−rnorm(20,1,0.05)输出结果df2
y1 y2 y3 y41 1.0141018 0.9238429 0.9420311 1.0009205
2 1.0258060 0.9940841 1.0183309 1.0953612
3 0.9743657 0.9705115 1.0517233 1.0596325
4 1.0199483 0.9521452 0.9873335 0.9910522
5 1.0740019 0.9531263 1.0805077 1.0352464
6 1.0504327 1.0587658 1.0105741 0.9503119
7 0.9656107 0.9558315 1.0856465 1.0721738
8 1.0314142 1.0368435 0.9007254 0.9555474
9 0.9688579 0.9117594 0.9920891 0.9693772
10 0.9811555 1.0072615 0.9550110 0.9611265
11 0.9594506 0.9935137 0.9792084 0.9442541
12 0.9891804 1.0018355 0.8821927 1.0816134
13 1.0939416 0.9531882 1.0682660 0.9552987
14 1.0437989 0.8805634 1.0034599 0.9708994
15 0.9660916 1.0378592 0.9780202 0.9961647
16 1.0634504 1.0431174 1.0184935 1.0586482
17 0.9907623 1.0666330 1.0507246 0.9516461
18 1.0336085 0.9449561 0.9972536 0.9815386
19 1.0366192 0.9172270 1.0393763 0.9332535
20 1.0861114 0.9739211 1.0502028 0.9452250
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