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dplyr:使用poly函数生成多项式系数

poly tidyverse dplyr r

3

MYaseen208 · 技术社区 · 7 年前

df1 <- 
  structure(list(
    Y = c(4, 4, 4, 4, 4, 8, 8, 8, 8, 8, 16, 16, 16, 
          16, 16, 32, 32, 32, 32, 32, 4, 4, 4, 4, 4, 8, 8, 8, 8, 8, 16, 
          16, 16, 16, 16, 32, 32, 32, 32, 32, 4, 4, 4, 4, 4, 8, 8, 8, 8, 
          8, 16, 16, 16, 16, 16, 32, 32, 32, 32, 32)), 
    class = "data.frame", row.names = c(NA, -60L))

library(tidyverse)
df1 %>%
  dplyr::mutate(
    Linear    = poly(x = Y, degree = 3, raw = TRUE)[ ,1]
  , Quadratic = poly(x = Y, degree = 3, raw = TRUE)[ ,2]  
  , Cubic     = poly(x = Y, degree = 3, raw = TRUE)[ ,3]
    )

我想知道是否有这样一种简洁的方法

df1 %>%
  dplyr::mutate(poly(x = Y, degree = 3, raw = TRUE))

谢谢

2 回复 | 直到 7 年前

1

7

acylam 7 年前

不完全是你所希望的,但足够接近。我首先转换 poly !!! 拼接列(将list/data.frame的每个元素转换为自己的参数)。 setNames

library(dplyr)

df1 %>%
  mutate(!!!as.data.frame(poly(x = .$Y, degree = 3, raw = TRUE))) %>%
  setNames(c("Y", "Linear", "Quadratic", "Cubic"))

结果:

    Y Linear Quadratic Cubic
1   4      4        16    64
2   4      4        16    64
3   4      4        16    64
4   4      4        16    64
5   4      4        16    64
6   8      8        64   512
7   8      8        64   512
8   8      8        64   512
9   8      8        64   512
10  8      8        64   512
11 16     16       256  4096
12 16     16       256  4096
13 16     16       256  4096
14 16     16       256  4096
15 16     16       256  4096
16 32     32      1024 32768
17 32     32      1024 32768
18 32     32      1024 32768
19 32     32      1024 32768
20 32     32      1024 32768
...

2

zack 7 年前

另一个选择,尽管我非常喜欢@useR的解决方案:

df1 %>%
  left_join(data.frame(Y = unique(.$Y), poly(unique(.$Y), degree = 3, raw = TRUE)),
            by = c('Y' = 'Y')) %>% 
  setNames(c('Y', 'Linear', 'Quadratic', 'Cubic'))

    Y Linear Quadratic Cubic
1   4      4        16    64
2   4      4        16    64
3   4      4        16    64
4   4      4        16    64
5   4      4        16    64
6   8      8        64   512
7   8      8        64   512
8   8      8        64   512
9   8      8        64   512
10  8      8        64   512
11 16     16       256  4096
12 16     16       256  4096
13 16     16       256  4096
14 16     16       256  4096
15 16     16       256  4096
16 32     32      1024 32768
17 32     32      1024 32768
18 32     32      1024 32768
19 32     32      1024 32768
20 32     32      1024 32768