如何根据管道中的行号选择列中的值

How to pick a value in a column based on row number within a pipeline

这个问题更多的是帮助我为我的代码构建一个高效的管道。

数据

df <- data.frame(stringsAsFactors=FALSE,
                 Date = c("2015-10-26", "2015-10-26", "2015-10-26", "2015-10-26",
                          "2015-10-27", "2015-10-27", "2015-10-27"),
                 Ticker = c("ANZ", "CBA", "NAB", "WBC", "ANZ", "CBA", "WBC"),
                 Open = c(29.11, 77.89, 32.69, 31.87, 29.05, 77.61, 31.84),
                 High = c(29.17, 77.93, 32.76, 31.92, 29.08, 78.1, 31.95),
                 Low = c(28.89, 77.37, 32.42, 31.71, 28.9, 77.54, 31.65),
                 Close = c(28.9, 77.5, 32.42, 31.84, 28.94, 77.74, 31.77),
                 Volume = c(6350170L, 2251288L, 3804239L, 5597684L, 5925519L, 2424679L,
                            5448863L)
)

这就是我希望我的工作流程的样子

df %>%
  mutate(new column = some_function(Open, 1))  # "Open" is column name, "1" is for row no.

应该输出以下内容:

Date         Ticker  Open  High   Low Close  Volume new_column
1 2015-10-26    ANZ 29.11 29.17 28.89 28.90 6350170      29.11
2 2015-10-26    CBA 77.89 77.93 77.37 77.50 2251288      29.11
3 2015-10-26    NAB 32.69 32.76 32.42 32.42 3804239      29.11
4 2015-10-26    WBC 31.87 31.92 31.71 31.84 5597684      29.11
5 2015-10-27    ANZ 29.05 29.08 28.90 28.94 5925519      29.11
6 2015-10-27    CBA 77.61 78.10 77.54 77.74 2424679      29.11
7 2015-10-27    WBC 31.84 31.95 31.65 31.77 5448863      29.11

想知道 some_functiontidyverse

中是什么

寻找head?

df %>%
  mutate(newcolumn = head(Open, 1))

另一种选择是仅使用 first 函数本身。如果 OP 正在从 dplyr 中寻找可以从一行中提供值的函数,那么该函数应该是 nth.

df %>%
    mutate(newcolumn = first(Open))

OR 来自特定行的值

df %>%
      mutate(newcolumn = nth(Open, 5))

nth 是一个 dplyr 函数。

我认为 OP 想要指定 any 行号,而不仅仅是第一个元素。但是您可以使用标准 [ 子集运算符简单地执行此操作:

df <- data.frame(stringsAsFactors=FALSE,
                 Date = c("2015-10-26", "2015-10-26", "2015-10-26", "2015-10-26",
                          "2015-10-27", "2015-10-27", "2015-10-27"),
                 Ticker = c("ANZ", "CBA", "NAB", "WBC", "ANZ", "CBA", "WBC"),
                 Open = c(29.11, 77.89, 32.69, 31.87, 29.05, 77.61, 31.84),
                 High = c(29.17, 77.93, 32.76, 31.92, 29.08, 78.1, 31.95),
                 Low = c(28.89, 77.37, 32.42, 31.71, 28.9, 77.54, 31.65),
                 Close = c(28.9, 77.5, 32.42, 31.84, 28.94, 77.74, 31.77),
                 Volume = c(6350170L, 2251288L, 3804239L, 5597684L, 5925519L, 2424679L,
                            5448863L)
)
library(dplyr)
df %>%
  mutate(new_column = Open[5])
#>         Date Ticker  Open  High   Low Close  Volume new_column
#> 1 2015-10-26    ANZ 29.11 29.17 28.89 28.90 6350170      29.05
#> 2 2015-10-26    CBA 77.89 77.93 77.37 77.50 2251288      29.05
#> 3 2015-10-26    NAB 32.69 32.76 32.42 32.42 3804239      29.05
#> 4 2015-10-26    WBC 31.87 31.92 31.71 31.84 5597684      29.05
#> 5 2015-10-27    ANZ 29.05 29.08 28.90 28.94 5925519      29.05
#> 6 2015-10-27    CBA 77.61 78.10 77.54 77.74 2424679      29.05
#> 7 2015-10-27    WBC 31.84 31.95 31.65 31.77 5448863      29.05

reprex package (v0.2.0) 创建于 2018-03-16。