开始使用 plyr `m*ply` 但无法重现示例

发布于 2024-10-10 08:50:21 字数 892 浏览 3 评论 0原文

该指南说代码位于文件 plyr.r 中，但我在哪里可以找到该文件。

但复制第一个示例似乎很容易，所以我决定尝试一下：

alt text

dat <- data.frame(c(10,100,50), mean=c(5,5,10), sd=c(1,2,1))
maply(dat, rnorm)

我明白了错误：

Error in function (..., na.last = TRUE, decreasing = FALSE)  : 
unimplemented type 'list' in 'orderVector1'

尝试

dat <- cbind(c(10,100,50), mean=c(5,5,10), sd=c(1,2,1))
maply(dat, rnorm)

会提出

Error: Results must have the same dimensions.

问题：

我做错了什么？
在哪里可以找到 plyr.r？（它不是这里）

原文

Trying to learn plyr, I have gotten stuck trying to reproduce code from the introductory guide.

The guide says that the code is in a file plyr.r, but not where I can find this file.

But reproducing one of the first examples seemed easy enough, so I decided to give it a try:

alt text

dat <- data.frame(c(10,100,50), mean=c(5,5,10), sd=c(1,2,1))
maply(dat, rnorm)

and I get this error:

Error in function (..., na.last = TRUE, decreasing = FALSE)  : 
unimplemented type 'list' in 'orderVector1'

trying

dat <- cbind(c(10,100,50), mean=c(5,5,10), sd=c(1,2,1))
maply(dat, rnorm)

gives

Error: Results must have the same dimensions.

questions:

what am I doing wrong?
where can I find plyr.r? (it is not here)

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晨光如昨 2024-10-17 08:50:21

您制作的数据框具有与 rnorm 函数不兼容的标头 (col.names)。请参阅：

> dat <- data.frame(c(10,100,50), mean=c(5,5,10), sd=c(1,2,1))
> dat
  c.10..100..50. mean sd
1             10    5  1
2            100    5  2
3             50   10  1

并且 m*pply 函数不知道如何处理 'c.10..100..50...' 列。

正如您在文档 (?mdply) 中看到的，以下示例非常有用：

> mdply(data.frame(mean = 1:5, sd = 1:5), rnorm, n = 2)
  mean sd         V1         V2
1    1  1 0.09919179  0.6083586
2    2  2 0.92787891 -0.1139743
3    3  3 2.21236781  0.8029677
4    4  4 4.16506428  9.2477373
5    5  5 1.26558507 12.0633377

如果您确实想要使用不同参数进行不同数量的观察，则不应使用 mdply，因为矩阵/ data.frame 必须具有相同的列数。安装使用 mlply，例如：

> mlply(data.frame(n=1:5, mean = 1:5, sd = 1:5), rnorm)
您制作的数据框具有与 rnorm 函数不兼容的标头 (col.names)。请参阅：
> dat <- data.frame(c(10,100,50), mean=c(5,5,10), sd=c(1,2,1))
> dat
  c.10..100..50. mean sd
1             10    5  1
2            100    5  2
3             50   10  1

并且 m*pply 函数不知道如何处理 'c.10..100..50...' 列。
正如您在文档 (?mdply) 中看到的，以下示例非常有用：
> mdply(data.frame(mean = 1:5, sd = 1:5), rnorm, n = 2)
  mean sd         V1         V2
1    1  1 0.09919179  0.6083586
2    2  2 0.92787891 -0.1139743
3    3  3 2.21236781  0.8029677
4    4  4 4.16506428  9.2477373
5    5  5 1.26558507 12.0633377

如果您确实想要使用不同参数进行不同数量的观察，则不应使用 mdply，因为矩阵/ data.frame 必须具有相同的列数。安装使用 mlply，例如：
1`
[1] 1.053083

您制作的数据框具有与 rnorm 函数不兼容的标头 (col.names)。请参阅：
> dat <- data.frame(c(10,100,50), mean=c(5,5,10), sd=c(1,2,1))
> dat
  c.10..100..50. mean sd
1             10    5  1
2            100    5  2
3             50   10  1

并且 m*pply 函数不知道如何处理 'c.10..100..50...' 列。
正如您在文档 (?mdply) 中看到的，以下示例非常有用：
> mdply(data.frame(mean = 1:5, sd = 1:5), rnorm, n = 2)
  mean sd         V1         V2
1    1  1 0.09919179  0.6083586
2    2  2 0.92787891 -0.1139743
3    3  3 2.21236781  0.8029677
4    4  4 4.16506428  9.2477373
5    5  5 1.26558507 12.0633377

如果您确实想要使用不同参数进行不同数量的观察，则不应使用 mdply，因为矩阵/ data.frame 必须具有相同的列数。安装使用 mlply，例如：
2`
[1] -1.650090  2.239547

您制作的数据框具有与 rnorm 函数不兼容的标头 (col.names)。请参阅：
> dat <- data.frame(c(10,100,50), mean=c(5,5,10), sd=c(1,2,1))
> dat
  c.10..100..50. mean sd
1             10    5  1
2            100    5  2
3             50   10  1

并且 m*pply 函数不知道如何处理 'c.10..100..50...' 列。
正如您在文档 (?mdply) 中看到的，以下示例非常有用：
> mdply(data.frame(mean = 1:5, sd = 1:5), rnorm, n = 2)
  mean sd         V1         V2
1    1  1 0.09919179  0.6083586
2    2  2 0.92787891 -0.1139743
3    3  3 2.21236781  0.8029677
4    4  4 4.16506428  9.2477373
5    5  5 1.26558507 12.0633377

如果您确实想要使用不同参数进行不同数量的观察，则不应使用 mdply，因为矩阵/ data.frame 必须具有相同的列数。安装使用 mlply，例如：
3`
[1] -0.94697908 -1.11479730 -0.03467497

您制作的数据框具有与 rnorm 函数不兼容的标头 (col.names)。请参阅：
> dat <- data.frame(c(10,100,50), mean=c(5,5,10), sd=c(1,2,1))
> dat
  c.10..100..50. mean sd
1             10    5  1
2            100    5  2
3             50   10  1

并且 m*pply 函数不知道如何处理 'c.10..100..50...' 列。
正如您在文档 (?mdply) 中看到的，以下示例非常有用：
> mdply(data.frame(mean = 1:5, sd = 1:5), rnorm, n = 2)
  mean sd         V1         V2
1    1  1 0.09919179  0.6083586
2    2  2 0.92787891 -0.1139743
3    3  3 2.21236781  0.8029677
4    4  4 4.16506428  9.2477373
5    5  5 1.26558507 12.0633377

如果您确实想要使用不同参数进行不同数量的观察，则不应使用 mdply，因为矩阵/ data.frame 必须具有相同的列数。安装使用 mlply，例如：
4`
[1]  6.427796  1.482655  1.436822 -5.993420

您制作的数据框具有与 rnorm 函数不兼容的标头 (col.names)。请参阅：
> dat <- data.frame(c(10,100,50), mean=c(5,5,10), sd=c(1,2,1))
> dat
  c.10..100..50. mean sd
1             10    5  1
2            100    5  2
3             50   10  1

并且 m*pply 函数不知道如何处理 'c.10..100..50...' 列。
正如您在文档 (?mdply) 中看到的，以下示例非常有用：
> mdply(data.frame(mean = 1:5, sd = 1:5), rnorm, n = 2)
  mean sd         V1         V2
1    1  1 0.09919179  0.6083586
2    2  2 0.92787891 -0.1139743
3    3  3 2.21236781  0.8029677
4    4  4 4.16506428  9.2477373
5    5  5 1.26558507 12.0633377

如果您确实想要使用不同参数进行不同数量的观察，则不应使用 mdply，因为矩阵/ data.frame 必须具有相同的列数。安装使用 mlply，例如：
5`
[1]  4.557689  6.217015  2.105255 -1.309664 -2.969184

attr(,"split_type")
[1] "array"
attr(,"split_labels")
  n mean sd
1 1    1  1
2 2    2  2
3 3    3  3
4 4    4  4
5 5    5  5

The data frame you made has a header (col.names) which is not compatible with the rnorm function. See:

> dat <- data.frame(c(10,100,50), mean=c(5,5,10), sd=c(1,2,1))
> dat
  c.10..100..50. mean sd
1             10    5  1
2            100    5  2
3             50   10  1

And the m*pply function do not know what to do with the 'c.10..100..50...' column.

As you can see in the docs (?mdply), the following example works like a charm:

> mdply(data.frame(mean = 1:5, sd = 1:5), rnorm, n = 2)
  mean sd         V1         V2
1    1  1 0.09919179  0.6083586
2    2  2 0.92787891 -0.1139743
3    3  3 2.21236781  0.8029677
4    4  4 4.16506428  9.2477373
5    5  5 1.26558507 12.0633377

If you really want different number of observations with the different parameters, you should not use mdply, because the matrix/data.frame must have the same number of columns. Insted use mlply, e.g.:

> mlply(data.frame(n=1:5, mean = 1:5, sd = 1:5), rnorm)
The data frame you made has a header (col.names) which is not compatible with the rnorm function. See:
> dat <- data.frame(c(10,100,50), mean=c(5,5,10), sd=c(1,2,1))
> dat
  c.10..100..50. mean sd
1             10    5  1
2            100    5  2
3             50   10  1

And the m*pply function do not know what to do with the 'c.10..100..50...' column.
As you can see in the docs (?mdply), the following example works like a charm:
> mdply(data.frame(mean = 1:5, sd = 1:5), rnorm, n = 2)
  mean sd         V1         V2
1    1  1 0.09919179  0.6083586
2    2  2 0.92787891 -0.1139743
3    3  3 2.21236781  0.8029677
4    4  4 4.16506428  9.2477373
5    5  5 1.26558507 12.0633377

If you really want different number of observations with the different parameters, you should not use mdply, because the matrix/data.frame must have the same number of columns. Insted use mlply, e.g.:
1`
[1] 1.053083

The data frame you made has a header (col.names) which is not compatible with the rnorm function. See:
> dat <- data.frame(c(10,100,50), mean=c(5,5,10), sd=c(1,2,1))
> dat
  c.10..100..50. mean sd
1             10    5  1
2            100    5  2
3             50   10  1

And the m*pply function do not know what to do with the 'c.10..100..50...' column.
As you can see in the docs (?mdply), the following example works like a charm:
> mdply(data.frame(mean = 1:5, sd = 1:5), rnorm, n = 2)
  mean sd         V1         V2
1    1  1 0.09919179  0.6083586
2    2  2 0.92787891 -0.1139743
3    3  3 2.21236781  0.8029677
4    4  4 4.16506428  9.2477373
5    5  5 1.26558507 12.0633377

If you really want different number of observations with the different parameters, you should not use mdply, because the matrix/data.frame must have the same number of columns. Insted use mlply, e.g.:
2`
[1] -1.650090  2.239547

The data frame you made has a header (col.names) which is not compatible with the rnorm function. See:
> dat <- data.frame(c(10,100,50), mean=c(5,5,10), sd=c(1,2,1))
> dat
  c.10..100..50. mean sd
1             10    5  1
2            100    5  2
3             50   10  1

And the m*pply function do not know what to do with the 'c.10..100..50...' column.
As you can see in the docs (?mdply), the following example works like a charm:
> mdply(data.frame(mean = 1:5, sd = 1:5), rnorm, n = 2)
  mean sd         V1         V2
1    1  1 0.09919179  0.6083586
2    2  2 0.92787891 -0.1139743
3    3  3 2.21236781  0.8029677
4    4  4 4.16506428  9.2477373
5    5  5 1.26558507 12.0633377

If you really want different number of observations with the different parameters, you should not use mdply, because the matrix/data.frame must have the same number of columns. Insted use mlply, e.g.:
3`
[1] -0.94697908 -1.11479730 -0.03467497

The data frame you made has a header (col.names) which is not compatible with the rnorm function. See:
> dat <- data.frame(c(10,100,50), mean=c(5,5,10), sd=c(1,2,1))
> dat
  c.10..100..50. mean sd
1             10    5  1
2            100    5  2
3             50   10  1

And the m*pply function do not know what to do with the 'c.10..100..50...' column.
As you can see in the docs (?mdply), the following example works like a charm:
> mdply(data.frame(mean = 1:5, sd = 1:5), rnorm, n = 2)
  mean sd         V1         V2
1    1  1 0.09919179  0.6083586
2    2  2 0.92787891 -0.1139743
3    3  3 2.21236781  0.8029677
4    4  4 4.16506428  9.2477373
5    5  5 1.26558507 12.0633377

If you really want different number of observations with the different parameters, you should not use mdply, because the matrix/data.frame must have the same number of columns. Insted use mlply, e.g.:
4`
[1]  6.427796  1.482655  1.436822 -5.993420

The data frame you made has a header (col.names) which is not compatible with the rnorm function. See:
> dat <- data.frame(c(10,100,50), mean=c(5,5,10), sd=c(1,2,1))
> dat
  c.10..100..50. mean sd
1             10    5  1
2            100    5  2
3             50   10  1

And the m*pply function do not know what to do with the 'c.10..100..50...' column.
As you can see in the docs (?mdply), the following example works like a charm:
> mdply(data.frame(mean = 1:5, sd = 1:5), rnorm, n = 2)
  mean sd         V1         V2
1    1  1 0.09919179  0.6083586
2    2  2 0.92787891 -0.1139743
3    3  3 2.21236781  0.8029677
4    4  4 4.16506428  9.2477373
5    5  5 1.26558507 12.0633377

If you really want different number of observations with the different parameters, you should not use mdply, because the matrix/data.frame must have the same number of columns. Insted use mlply, e.g.:
5`
[1]  4.557689  6.217015  2.105255 -1.309664 -2.969184

attr(,"split_type")
[1] "array"
attr(,"split_labels")
  n mean sd
1 1    1  1
2 2    2  2
3 3    3  3
4 4    4  4
5 5    5  5