根据条件仅将 R 中的某些行转换为绝对值
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【中文标题】根据条件仅将 R 中的某些行转换为绝对值【英文标题】：Convert into absolute values only certain rows in R based on conditions 【发布时间】：2021-07-28 16:14:51 【问题描述】：我有这个数据集
df <- data.frame(PatientID = c("0002" ,"0002", "0005", "0005" ,"0009" ,"0009" ,"0018", "0018" ,"0020" ,"0027", "0039" ,"0039" ,"0042", "0043" ,"0043" ,"0045", "0046", "0046" ,"0048" ,"0048", "0055"),
Timepoint= c("A", "B", "A", "B", "A", "B", "A", "B", "A", "A", "A", "B", "A", "A", "B", "A", "A", "B", "A", "B", "A"),
A = c(NA , 977.146 , NA , 964.315 ,NA , 952.311 , NA , 950.797 , 958.975 ,960.712 ,NA , 947.465 , -902.852 , NA, 985.124 ,NA , 930.141 ,-1007.790 , 948.848, 1027.110 , -999.414),
B = c(998.988 , NA , 998.680 , NA , NA ,1020.560 , 947.751 ,1029.560 , 955.540 , 911.606 , 964.039 , NA, 988.087 , -902.367 , 959.338 ,1029.050 , 925.162 , 987.374 ,1066.400 ,957.512 , 917.597),
C = c( NA , 987.140 , 961.810 , 929.466 , 978.166, 1005.820 ,925.752 , -969.469 , 943.398 ,936.034, -965.292 , 996.404 , 920.610 , 967.047 ,986.565 , 913.517 , -893.428 , 921.606 , NA , 929.590 ,950.493),
D = c(975.634 , 987.140 , 961.810 , 929.466 , 978.166, 1005.820 , 925.752 , 969.469 ,943.398 , NA , 965.292 , 996.404 , NA , 967.047 , 986.565 , NA , 893.428 , 921.606 , 976.192 , 929.590 , 950.493),
E = c(1006.330, -1028.070 , NA , -954.274 ,1005.910 ,949.969 , 992.820 , 977.048 ,934.407 , 948.913 , NA , NA , NA, 961.375 ,-955.296 , 961.128 ,998.119 ,1009.110 , 994.891 ,-1000.170 ,982.763),
G= c(NA , 958.990 , NA , NA , 924.680 , 955.927 , NA , 949.384 ,973.348 , -984.392 , 943.894 , 961.468 , -995.368 , 994.997 , NA , -979.454 , 952.605 , NA , NA, NA , 956.507), stringsAsFactors = F)
而且我只需要将属于df$Timepoint==B的数字转换为绝对值
你有什么推荐的？
谢谢
【问题讨论】：
【参考方案1】：我们可以使用 dplyr 和 mutate() 以及 cross() 和 ifelse() 将条件合并到单个衬里，而无需创建中间对象：
df %>% mutate(across(A:G, ~ifelse(Timepoint=='B', abs(.x), .x)))
PatientID Timepoint A B C D E G
1 0002 A NA 998.988 NA 975.634 1006.330 NA
2 0002 B 977.146 NA 987.140 987.140 1028.070 958.990
3 0005 A NA 998.680 961.810 961.810 NA NA
4 0005 B 964.315 NA 929.466 929.466 954.274 NA
5 0009 A NA NA 978.166 978.166 1005.910 924.680
6 0009 B 952.311 1020.560 1005.820 1005.820 949.969 955.927
7 0018 A NA 947.751 925.752 925.752 992.820 NA
8 0018 B 950.797 1029.560 969.469 969.469 977.048 949.384
9 0020 A 958.975 955.540 943.398 943.398 934.407 973.348
10 0027 A 960.712 911.606 936.034 NA 948.913 -984.392
11 0039 A NA 964.039 -965.292 965.292 NA 943.894
12 0039 B 947.465 NA 996.404 996.404 NA 961.468
13 0042 A -902.852 988.087 920.610 NA NA -995.368
14 0043 A NA -902.367 967.047 967.047 961.375 994.997
15 0043 B 985.124 959.338 986.565 986.565 955.296 NA
16 0045 A NA 1029.050 913.517 NA 961.128 -979.454
17 0046 A 930.141 925.162 -893.428 893.428 998.119 952.605
18 0046 B 1007.790 987.374 921.606 921.606 1009.110 NA
19 0048 A 948.848 1066.400 NA 976.192 994.891 NA
20 0048 B 1027.110 957.512 929.590 929.590 1000.170 NA
21 0055 A -999.414 917.597 950.493 950.493 982.763 956.507
【讨论】：
这不太行，因为 B 值仍然显示负值？ - 感谢您的回答！ 我复制了错误的输出数据，但代码没问题。请看现在是否可以【参考方案2】：我不确定这是否是你想要的，但你可以使用这个：
df[df$Timepoint=="B",c(3:8)] <- apply(df[df$Timepoint=="B",c(3:8)], 2, abs)
或
columns <- c("A", "B", "C", "D", "E", "G")
df[df$Timepoint=="B",columns] <- apply(df[df$Timepoint=="B",columns], 2, abs)
【讨论】：
【参考方案3】：这是一个 data.table 解决方案：
setDT(df)
cols <- sapply(df, is.numeric)
cols <- names(cols)[cols]
df[Timepoint == 'B', (cols) := lapply(.SD, FUN = abs),.SDcols = cols]
【讨论】：
请注意.SDcols 接受一个函数来选择列，即.SDcols = is.numeric 就足够了。干杯【参考方案4】：
不是世界上最高效的代码，但这会起作用
df$A[df$Timepoint == "B"] <- abs(df$A)
df$B[df$Timepoint == "B"] <- abs(df$B)
df$C[df$Timepoint == "B"] <- abs(df$C)
df$D[df$Timepoint == "B"] <- abs(df$D)
df$E[df$Timepoint == "B"] <- abs(df$E)
df$G[df$Timepoint == "B"] <- abs(df$G)
【讨论】：
这对任何人来说都不是一个有用的解决方案以上是关于根据条件仅将 R 中的某些行转换为绝对值的主要内容，如果未能解决你的问题，请参考以下文章