如何根据每行中R中的另一列/另一列替换几列的值？答案

【问题标题】：How to replace values of several columns based on/ another column in R within each row?如何根据每行中R中的另一列/另一列替换几列的值？
【发布时间】：2021-06-21 22:02:51
【问题描述】：

我正在处理一个数据集 (30000 x 500 )，我需要根据另一列的数据替换列中的一些值。问题是在每一行中，参考值都会发生变化。这是数据集的一个子示例：

#Create a data frame
df <- data.frame(SNP = c("SNP1","SNP2","SNP3","SNP4","SNP5","SNP6","SNP7","SNP8","SNP9","SNP10"), 
                   A_allele = c("C","G","C","G","C","C","A","T","G","C"),
                   B_allele = c("G","A","T","A","A","G","T","A","C","A"),
                   alleles = c("C/G","G/A","C/T","G/A","C/A","C/G","A/T","T/A","G/C","C/A"),
                   line_1 = sample(c("A","B"),10, replace = TRUE),
                   line_2 = sample(c("A","B"),10, replace = TRUE),
                   line_3 = sample(c("A","B"),10, replace = TRUE),
                   line_4 = sample(c("A","B"),10, replace = TRUE),
                   line_5 = sample(c("A","B"),10, replace = TRUE),
                   line_6 = sample(c("A","B"),10, replace = TRUE),
                   line_7 = sample(c("A","B"),10, replace = TRUE),
                   line_8 = sample(c("A","B"),10, replace = TRUE),
                   line_9 = sample(c("A","B"),10, replace = TRUE),
                   line_10 = sample(c("A","B"),10, replace = TRUE)
                   )

df
head(df)
     SNP A_allele B_allele alleles line_1 line_2 line_3 line_4 line_5 line_6 line_7 line_8 line_9 line_10
1   SNP1        C        G     C/G      B      A      B      A      B      B      B      B      B       A
2   SNP2        G        A     G/A      A      B      A      A      A      B      B      A      B       A
3   SNP3        C        T     C/T      B      B      A      B      B      B      A      A      A       A
4   SNP4        G        A     G/A      A      B      B      A      B      A      B      B      B       A
5   SNP5        C        A     C/A      B      A      B      B      B      A      B      A      B       B
6   SNP6        C        G     C/G      B      A      B      A      B      A      B      B      B       B
7   SNP7        A        T     A/T      B      A      A      B      A      A      B      A      B       A
8   SNP8        T        A     T/A      A      B      A      B      A      A      B      B      A       B
9   SNP9        G        C     G/C      B      A      B      B      B      B      A      B      A       B
10 SNP10        C        A     C/A      B      B      B      B      B      A      A      A      A       A

对于每一行，A_allele 和 B_allele 列作为参考值来更改 10 行中的 A 或 B 值。当存在“A”值时 => 使用列 A_allele 中的值，当存在“B”值时 => 使用列_B 中的值。

在示例中，应如下所示：

第 1 行：将 A 行更改为 C / 将 B 行更改为 G
第 2 行：将 A 行更改为 G / 将 B 行更改为 A
第 3 行：将 A 行更改为 C / 将 B 行更改为 T
第 10 行：同样的想法。

输出应该是这样的：

SNP A_allele B_allele alleles line_1 line_2 line_3 line_4 line_5 line_6 line_7 line_8 line_9 line_10
1   SNP1    C   G   C/G G   C   G   C   G   G   G   G   G   C
2   SNP2    G   A   G/A G   A   G   G   G   A   A   G   A   G
3   SNP3    C   T   C/T T   T   C   T   T   T   C   C   C   C
4   SNP4    G   A   G/A G   A   A   G   A   G   A   A   A   G
5   SNP5    C   A   C/A A   C   A   A   A   C   A   C   A   A
6   SNP6    C   G   C/G G   C   G   C   G   C   G   G   G   G
7   SNP7    A   T   A/T T   A   A   T   A   A   T   A   T   A
8   SNP8    T   A   T/A T   A   T   A   T   T   A   A   T   A
9   SNP9    G   C   G/C C   G   C   C   C   C   G   C   G   C
10  SNP10   C   A   C/A A   A   A   A   A   C   C   C   C   C

由于大约有 30000 行，如果可能的话，我想要一个高效的代码来运行。

有什么建议吗？

【问题讨论】：

标签： r dataframe if-statement conditional-statements

【解决方案1】：

你可以的

library(tidyverse)

df %>% mutate(across(starts_with("line"), ~ifelse(. == "A", str_sub(alleles, 1, 1), str_sub(alleles, 3, 3))))

#output with df generated with set.seed(2021)
     SNP A_allele B_allele alleles line_1 line_2 line_3 line_4 line_5 line_6 line_7 line_8 line_9 line_10
1   SNP1        C        G     C/G      C      C      G      C      C      C      G      G      C       G
2   SNP2        G        A     G/A      A      A      A      A      G      G      G      G      G       G
3   SNP3        C        T     C/T      T      T      C      C      T      T      T      T      T       C
4   SNP4        G        A     G/A      A      G      A      A      A      G      G      A      G       A
5   SNP5        C        A     C/A      C      C      C      A      C      A      A      C      C       A
6   SNP6        C        G     C/G      G      C      C      C      C      C      G      C      G       G
7   SNP7        A        T     A/T      T      A      T      T      T      T      T      A      T       A
8   SNP8        T        A     T/A      A      T      A      T      A      A      A      T      A       T
9   SNP9        G        C     G/C      C      C      C      C      C      G      G      G      C       C
10 SNP10        C        A     C/A      A      C      A      C      A      C      C      C      C       A

如 cmets 中所述，如果列名不遵循模式，Option-1 您可以将它们存储在一个向量中，比如 vars，并在 across 中使用它

set.seed(2021)
df <- data.frame(SNP = c("SNP1","SNP2","SNP3","SNP4","SNP5","SNP6","SNP7","SNP8","SNP9","SNP10"), 
                 A_allele = c("C","G","C","G","C","C","A","T","G","C"),
                 B_allele = c("G","A","T","A","A","G","T","A","C","A"),
                 alleles = c("C/G","G/A","C/T","G/A","C/A","C/G","A/T","T/A","G/C","C/A"),
                 line_1 = sample(c("A","B"),10, replace = TRUE),
                 line_2 = sample(c("A","B"),10, replace = TRUE),
                 line_3 = sample(c("A","B"),10, replace = TRUE),
                 line_4 = sample(c("A","B"),10, replace = TRUE),
                 line_5 = sample(c("A","B"),10, replace = TRUE),
                 line_6 = sample(c("A","B"),10, replace = TRUE),
                 line_7 = sample(c("A","B"),10, replace = TRUE),
                 cat = sample(c("A","B"),10, replace = TRUE),
                 dog = sample(c("A","B"),10, replace = TRUE),
                 rabbit = sample(c("A","B"),10, replace = TRUE)
)

vars <- c("line_1", "line_2", "line_3", "line_4", "line_5", "line_6", "line_7", "cat", "dog", "rabbit")

df %>% mutate(across(.cols = vars, ~ifelse(. == "A", str_sub(alleles, 1, 1), str_sub(alleles, 3, 3))))

Note: Using an external vector in selections is ambiguous.
i Use `all_of(vars)` instead of `vars` to silence this message.
i See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
This message is displayed once per session.
     SNP A_allele B_allele alleles line_1 line_2 line_3 line_4 line_5 line_6 line_7 cat dog rabbit
1   SNP1        C        G     C/G      C      C      G      C      C      C      G   G   C      G
2   SNP2        G        A     G/A      A      A      A      A      G      G      G   G   G      G
3   SNP3        C        T     C/T      T      T      C      C      T      T      T   T   T      C
4   SNP4        G        A     G/A      A      G      A      A      A      G      G   A   G      A
5   SNP5        C        A     C/A      C      C      C      A      C      A      A   C   C      A
6   SNP6        C        G     C/G      G      C      C      C      C      C      G   C   G      G
7   SNP7        A        T     A/T      T      A      T      T      T      T      T   A   T      A
8   SNP8        T        A     T/A      A      T      A      T      A      A      A   T   A      T
9   SNP9        G        C     G/C      C      C      C      C      C      G      G   G   C      C
10 SNP10        C        A     C/A      A      C      A      C      A      C      C   C   C      A

Option-2你也可以直接列索引

df %>% mutate(across(5:14, ~ifelse(. == "A", str_sub(alleles, 1, 1), str_sub(alleles, 3, 3))))

     SNP A_allele B_allele alleles line_1 line_2 line_3 line_4 line_5 line_6 line_7 cat dog rabbit
1   SNP1        C        G     C/G      C      C      G      C      C      C      G   G   C      G
2   SNP2        G        A     G/A      A      A      A      A      G      G      G   G   G      G
3   SNP3        C        T     C/T      T      T      C      C      T      T      T   T   T      C
4   SNP4        G        A     G/A      A      G      A      A      A      G      G   A   G      A
5   SNP5        C        A     C/A      C      C      C      A      C      A      A   C   C      A
6   SNP6        C        G     C/G      G      C      C      C      C      C      G   C   G      G
7   SNP7        A        T     A/T      T      A      T      T      T      T      T   A   T      A
8   SNP8        T        A     T/A      A      T      A      T      A      A      A   T   A      T
9   SNP9        G        C     G/C      C      C      C      C      C      G      G   G   C      C
10 SNP10        C        A     C/A      A      C      A      C      A      C      C   C   C      A

【讨论】：

非常感谢！知道如何选择不共享任何常见模式（即行）的列。我的台词名称不同（狗、猫、鸟、猴子等），我只使用这些名称作为参考。谢谢
感谢您的澄清。我使用 vars

【解决方案2】：

您可以在dplyr 中使用across 和ifelse。

library(dplyr)
df %>% mutate(across(starts_with('line'), ~ifelse(. == 'A', A_allele, B_allele)))

或lapply 在基础 R 中：

cols <- grep('line', names(df))
df[cols] <- lapply(df[cols], function(x) ifelse(x == 'A', df$A_allele, df$B_allele))

【讨论】：

感谢您的回复，但我有两个 cmets： 1. 我得到的是数字而不是 C/G/A/T。例如，SNP1 有 3 3 3 2 2 3 2 3 3 而不是 G G C C。数字看起来与有序字母 1 = A 相同； 2 = C; 3 = G; 4 = T 但不确定。 2. 如果线条没有相似的图案（即线条）并且有很大的不同，例如猫、狗、猴子、鸟等，我用线条来简化解释，但名称本来就不同，没有共同的图案。
@Javier_HV 我认为您在 R data.frame 调用中添加stringsAsFactors = FALSE。
是的，你是对的，包括字符串作为因素。关于第二点，选择不共享任何共同模式（即行）的列的任何想法。我的台词名称不同，我只使用这些名称作为参考。谢谢
如何确定要更改的列？您可以使用数字索引。 cols <- 5:14 或者如果没有共同点，您可能需要手动将它们添加到向量中。 cols <- c(1, 3, 4, 5, 8) 等。在lapply 解决方案中使用此cols，并在across 中将starts_with('line') 替换为cols。