多列字符串匹配与关联名称中的特定字符串和值比较
String matching over multiple columns with specific strings and value comparisons in associated names
我对跨一系列列进行字符串检测和值比较感兴趣。如果在列中找到字符串（在本例中为 ZSD），则需要比较它们在另一列中的对应值。
输入
我的输入如下：
a.zsd a.test b.zsd b.test c.zsd c.test d.zsd d.test
'ZSD' 0.0 'ZAD' 1.0 NA 0.5 'ZAD' 1.0
'ZAD' 1.0 NA 0.0 NA 0.5 'ZSD' 0.0
NA 0.5 NA 0.5 'ZAD' 0.5 NA 0.5
'Not Achieved ZSD' 0.0 NA 0.5 'ZAD' 0.5 NA 0.5
'ZSD' 1.0 'ZSD' 0.5 NA 0.5 'ZSD' 0.0
NA 0.0 NA 0.0 NA 0.5 NA 0.0
NA 1.0 'ZSD' 0.0 'ZSD' 0.5 'ZSD' 1.0
输出
在我的输出中，我想要另外两列 smallest.test 和 zsd.level:
a.zsd a.test b.zsd b.test c.zsd c.test d.zsd d.test smallest.test zsd.level
'ZSD' 0.0 'ZAD' 1.0 NA 0.5 'ZAD' 1.0 0.0 a
'ZAD' 1.0 NA 0.0 NA 0.5 'ZSD' 0.0 0.0 d
NA 0.5 NA 0.5 'ZAD' 0.5 NA 0.5 0.0 NA
'Not Achieved ZSD' 0.0 NA 0.5 'ZAD' 0.5 NA 0.5 0.0 a
'ZSD' 1.0 'ZSD' 0.5 NA 0.5 'ZSD' 0.0 0.0 d
NA 0.0 NA 0.0 NA 0.5 NA 0.0 0.0 NA
NA 1.0 'ZSD' 0.0 'ZSD' 0.5 'ZSD' 1.0 0.0 b
信息：
我的数据框有一百多列。我只对名称以字符串 .zsd 结尾的一些列感兴趣。这些列可以具有 NA 或以下字符串值之一 ZAD、ZSD、Not Achieved ZSD。具有 .zsd 字符串名称的每一列都有一个关联的 .test 列。
要求
我想在输出中添加两个新列 smallest.test 和 zsd.level。要求如下：
遍历以字符串 .zsd
结尾的列名
在这些列中检测字符串 ZSD
如果仅在其中一列中找到 ZSD 字符串，return 输出列中该列的名称 zsd.level 以及 return 以 .test 结尾的列名称中的对应值将被 return 编辑到输出列 smallest.test。
如果none列包含字符串ZSD，return输出列zsd.level和return0.0在相应的输出列中 smallest.test.
如果不止一列包含字符串ZSD，在输出中选择相应.test列和return值最小的列。
如果不止一个列包含字符串 ZSD，并且它们都具有相应 .test 列的相同值，则选择最后一个列名作为输出以及输出的 .test 的相应值。
dput()
dput(df)
structure(list(a.zsd = c("ZSD", "ZAD", NA, "Not Achieved ZSD", "ZSD", NA, NA),
a.test = c(0, 1, 0.5, 0, 1, 0, 1),
b.zsd = c("ZAD", NA, NA, NA, "ZSD", NA, "ZSD"),
b.test = c(1, 0, 0.5, 0.5, 0.5, 0, 0),
c.zsd = c(NA, NA, "ZAD", "ZAD", NA, NA, "ZSD"),
c.test = c(0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5),
d.zsd = c("ZAD", "ZSD", NA, NA, "ZSD", NA, "ZSD"),
d.test = c(1, 0, 0.5, 0.5, 0, 0, 1)),
class = "data.frame", row.names = c(NA, -7L))
部分解决方案
基于以下post：，此代码可以迭代并select .zsd 列和return 中最高的列名输出。但它没有考虑 .test 字段的相应值。如有任何帮助，我们将不胜感激。
library(dplyr)
library(tidyr)
library(stringr)
df %>%
mutate(across(contains("zsd"), ~case_when(str_detect(., "ZSD") ~ cur_column()), .names = 'new_{col}')) %>%
unite(zsd_level, starts_with('new'), na.rm = TRUE, sep = ' ') %>%
mutate(zsd_level = str_remove_all(zsd_level, ".zsd"),
zsd_level = str_sub(zsd_level, -1))
这是一个涉及 which.min 的 base 解决方案，它假定相应的“.test”和“.zsd”列是相邻的。
第一个代码块可用于此目的，但如果给定行在最小值中有联系，它将给出第一个实例。下面是一个函数，可用于 select 最小值的第一个或最后一个实例。
# sample data
df <- structure(list(a.zsd = c("ZSD", "ZAD", NA, "Not Achieved ZSD", "ZSD", NA, NA),
a.test = c(0, 1, 0.5, 0, 1, 0, 1),
b.zsd = c("ZAD", NA, NA, NA, "ZSD", NA, "ZSD"),
b.test = c(1, 0, 0.5, 0.5, 0.5, 0, 0),
c.zsd = c(NA, NA, "ZAD", "ZAD", NA, NA, "ZSD"),
c.test = c(0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5),
d.zsd = c("ZAD", "ZSD", NA, NA, "ZSD", NA, "ZSD"),
d.test = c(1, 0, 0.5, 0.5, 0, 0, 1)),
class = "data.frame", row.names = c(NA, -7L))
# select .zsd columns
zsd_cols <- grep(".zsd", names(df), value = TRUE)
zsd_df <- df[, zsd_cols]
# select .test columns
test_cols <- gsub("zsd", "test",zsd_cols)
test_df <- df[, test_cols]
# convert "Not Achieved ZSD" to "ZSD"
zsd_df[zsd_df == "Not Achieved ZSD" ] <- "ZSD"
# assign NA to non "ZSD" cells
zsd_df[zsd_df != "ZSD"] <- NA
# assign 999 test_df values whose corresponding zsd_df is NA
test_df[is.na(zsd_df)] <- 999
# return cols which hold minimum
nams <- names(test_df)[apply(test_df, 1 ,which.min)]
# scrub .test suffix
nams <- gsub(".test", "", nams)
# return mins
mins <- apply(test_df, 1 ,min)
# assign values less than 999 as smallest test, or zero
df$smallest.test <- ifelse(mins < 999, mins, 0)
# assign name if corresponding min less than 999 or NA
df$zsd_level <- ifelse(mins < 999, nams, NA)
> df
a.zsd a.test b.zsd b.test c.zsd c.test d.zsd d.test smallest.test zsd_level
1 ZSD 0.0 ZAD 1.0 <NA> 0.5 ZAD 1.0 0 a
2 ZAD 1.0 <NA> 0.0 <NA> 0.5 ZSD 0.0 0 d
3 <NA> 0.5 <NA> 0.5 ZAD 0.5 <NA> 0.5 0 <NA>
4 Not Achieved ZSD 0.0 <NA> 0.5 ZAD 0.5 <NA> 0.5 0 a
5 ZSD 1.0 ZSD 0.5 <NA> 0.5 ZSD 0.0 0 d
6 <NA> 0.0 <NA> 0.0 <NA> 0.5 <NA> 0.0 0 <NA>
7 <NA> 1.0 ZSD 0.0 ZSD 0.5 ZSD 1.0 0 b
编辑
相同的想法，但是一个函数可以在连续存在关系时获得第一个或最后一个最小值：
# adjusted sample data
df <- data.frame(a.zsd = c("ZSD", "ZAD", NA,
"Not Achieved ZSD", "ZSD", NA, NA),
a.test = c(0, 1, 0.5, 0, 1, 0, 1),
b.zsd = c("ZAD", NA, NA, NA, "ZSD", NA, "ZSD"),
b.test = c(1, 0, 0.5, 0.5, 0.0, 0, 0), # adjusted
c.zsd = c(NA, NA, "ZAD", "ZAD", NA, NA, "ZSD"),
c.test = c(0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5),
d.zsd = c("ZAD", "ZSD", NA, NA, "ZSD", NA, "ZSD"),
d.test = c(1, 0, 0.5, 0.5, 0, 0, 1))
appendMin <- function(df, last_min = TRUE){
# select .zsd columns
zsd_cols <- grep(".zsd", names(df), value = TRUE)
zsd_df <- df[, zsd_cols]
if(last_min) { zsd_df <- rev(zsd_df) } # for last min
# select .test columns
test_cols <- gsub("zsd", "test",zsd_cols)
test_df <- df[, test_cols]
if(last_min) { test_df <- rev(test_df) } # for last min
# convert "Not Achieved ZSD" to "ZSD"
zsd_df[zsd_df == "Not Achieved ZSD" ] <- "ZSD"
# assign NA to non "ZSD" cells
zsd_df[zsd_df != "ZSD" ] <- NA
# assign 999 test_df values whose corresponding zsd_df is NA
test_df[is.na(zsd_df)] <- 999
# return cols which hold the first minimum
nams <- names(test_df)[apply(test_df, 1 ,which.min)]
# scrub .test suffix
nams <- gsub(".test", "", nams)
# return mins
mins <- apply(test_df, 1 ,min)
# assign values less than 999 as smallest test, or zero
df$smallest.test <- ifelse(mins < 999, mins, 0)
# assign name if corresponding min less than 999 or NA
df$zsd_level <- ifelse(mins < 999, nams, NA)
return(df)
}
ties_first <- appendMin(df, last_min = FALSE)
ties_last <- appendMin(df, last_min = TRUE)
我对跨一系列列进行字符串检测和值比较感兴趣。如果在列中找到字符串（在本例中为 ZSD），则需要比较它们在另一列中的对应值。
输入
我的输入如下：
a.zsd a.test b.zsd b.test c.zsd c.test d.zsd d.test
'ZSD' 0.0 'ZAD' 1.0 NA 0.5 'ZAD' 1.0
'ZAD' 1.0 NA 0.0 NA 0.5 'ZSD' 0.0
NA 0.5 NA 0.5 'ZAD' 0.5 NA 0.5
'Not Achieved ZSD' 0.0 NA 0.5 'ZAD' 0.5 NA 0.5
'ZSD' 1.0 'ZSD' 0.5 NA 0.5 'ZSD' 0.0
NA 0.0 NA 0.0 NA 0.5 NA 0.0
NA 1.0 'ZSD' 0.0 'ZSD' 0.5 'ZSD' 1.0
输出
在我的输出中，我想要另外两列 smallest.test 和 zsd.level:
a.zsd a.test b.zsd b.test c.zsd c.test d.zsd d.test smallest.test zsd.level
'ZSD' 0.0 'ZAD' 1.0 NA 0.5 'ZAD' 1.0 0.0 a
'ZAD' 1.0 NA 0.0 NA 0.5 'ZSD' 0.0 0.0 d
NA 0.5 NA 0.5 'ZAD' 0.5 NA 0.5 0.0 NA
'Not Achieved ZSD' 0.0 NA 0.5 'ZAD' 0.5 NA 0.5 0.0 a
'ZSD' 1.0 'ZSD' 0.5 NA 0.5 'ZSD' 0.0 0.0 d
NA 0.0 NA 0.0 NA 0.5 NA 0.0 0.0 NA
NA 1.0 'ZSD' 0.0 'ZSD' 0.5 'ZSD' 1.0 0.0 b
信息：
我的数据框有一百多列。我只对名称以字符串 .zsd 结尾的一些列感兴趣。这些列可以具有 NA 或以下字符串值之一 ZAD、ZSD、Not Achieved ZSD。具有 .zsd 字符串名称的每一列都有一个关联的 .test 列。
要求
我想在输出中添加两个新列 smallest.test 和 zsd.level。要求如下：
遍历以字符串
结尾的列名.zsd在这些列中检测字符串
ZSD如果仅在其中一列中找到
ZSD字符串，return 输出列中该列的名称zsd.level以及 return 以.test结尾的列名称中的对应值将被 return 编辑到输出列smallest.test。如果none列包含字符串
ZSD，return输出列zsd.level和return0.0在相应的输出列中smallest.test.如果不止一列包含字符串
ZSD，在输出中选择相应.test列和return值最小的列。如果不止一个列包含字符串
ZSD，并且它们都具有相应.test列的相同值，则选择最后一个列名作为输出以及输出的.test的相应值。
dput()
dput(df)
structure(list(a.zsd = c("ZSD", "ZAD", NA, "Not Achieved ZSD", "ZSD", NA, NA),
a.test = c(0, 1, 0.5, 0, 1, 0, 1),
b.zsd = c("ZAD", NA, NA, NA, "ZSD", NA, "ZSD"),
b.test = c(1, 0, 0.5, 0.5, 0.5, 0, 0),
c.zsd = c(NA, NA, "ZAD", "ZAD", NA, NA, "ZSD"),
c.test = c(0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5),
d.zsd = c("ZAD", "ZSD", NA, NA, "ZSD", NA, "ZSD"),
d.test = c(1, 0, 0.5, 0.5, 0, 0, 1)),
class = "data.frame", row.names = c(NA, -7L))
部分解决方案
基于以下post：.zsd 列和return 中最高的列名输出。但它没有考虑 .test 字段的相应值。如有任何帮助，我们将不胜感激。
library(dplyr)
library(tidyr)
library(stringr)
df %>%
mutate(across(contains("zsd"), ~case_when(str_detect(., "ZSD") ~ cur_column()), .names = 'new_{col}')) %>%
unite(zsd_level, starts_with('new'), na.rm = TRUE, sep = ' ') %>%
mutate(zsd_level = str_remove_all(zsd_level, ".zsd"),
zsd_level = str_sub(zsd_level, -1))
这是一个涉及 which.min 的 base 解决方案，它假定相应的“.test”和“.zsd”列是相邻的。
第一个代码块可用于此目的，但如果给定行在最小值中有联系，它将给出第一个实例。下面是一个函数，可用于 select 最小值的第一个或最后一个实例。
# sample data
df <- structure(list(a.zsd = c("ZSD", "ZAD", NA, "Not Achieved ZSD", "ZSD", NA, NA),
a.test = c(0, 1, 0.5, 0, 1, 0, 1),
b.zsd = c("ZAD", NA, NA, NA, "ZSD", NA, "ZSD"),
b.test = c(1, 0, 0.5, 0.5, 0.5, 0, 0),
c.zsd = c(NA, NA, "ZAD", "ZAD", NA, NA, "ZSD"),
c.test = c(0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5),
d.zsd = c("ZAD", "ZSD", NA, NA, "ZSD", NA, "ZSD"),
d.test = c(1, 0, 0.5, 0.5, 0, 0, 1)),
class = "data.frame", row.names = c(NA, -7L))
# select .zsd columns
zsd_cols <- grep(".zsd", names(df), value = TRUE)
zsd_df <- df[, zsd_cols]
# select .test columns
test_cols <- gsub("zsd", "test",zsd_cols)
test_df <- df[, test_cols]
# convert "Not Achieved ZSD" to "ZSD"
zsd_df[zsd_df == "Not Achieved ZSD" ] <- "ZSD"
# assign NA to non "ZSD" cells
zsd_df[zsd_df != "ZSD"] <- NA
# assign 999 test_df values whose corresponding zsd_df is NA
test_df[is.na(zsd_df)] <- 999
# return cols which hold minimum
nams <- names(test_df)[apply(test_df, 1 ,which.min)]
# scrub .test suffix
nams <- gsub(".test", "", nams)
# return mins
mins <- apply(test_df, 1 ,min)
# assign values less than 999 as smallest test, or zero
df$smallest.test <- ifelse(mins < 999, mins, 0)
# assign name if corresponding min less than 999 or NA
df$zsd_level <- ifelse(mins < 999, nams, NA)
> df
a.zsd a.test b.zsd b.test c.zsd c.test d.zsd d.test smallest.test zsd_level
1 ZSD 0.0 ZAD 1.0 <NA> 0.5 ZAD 1.0 0 a
2 ZAD 1.0 <NA> 0.0 <NA> 0.5 ZSD 0.0 0 d
3 <NA> 0.5 <NA> 0.5 ZAD 0.5 <NA> 0.5 0 <NA>
4 Not Achieved ZSD 0.0 <NA> 0.5 ZAD 0.5 <NA> 0.5 0 a
5 ZSD 1.0 ZSD 0.5 <NA> 0.5 ZSD 0.0 0 d
6 <NA> 0.0 <NA> 0.0 <NA> 0.5 <NA> 0.0 0 <NA>
7 <NA> 1.0 ZSD 0.0 ZSD 0.5 ZSD 1.0 0 b
编辑
相同的想法，但是一个函数可以在连续存在关系时获得第一个或最后一个最小值：
# adjusted sample data
df <- data.frame(a.zsd = c("ZSD", "ZAD", NA,
"Not Achieved ZSD", "ZSD", NA, NA),
a.test = c(0, 1, 0.5, 0, 1, 0, 1),
b.zsd = c("ZAD", NA, NA, NA, "ZSD", NA, "ZSD"),
b.test = c(1, 0, 0.5, 0.5, 0.0, 0, 0), # adjusted
c.zsd = c(NA, NA, "ZAD", "ZAD", NA, NA, "ZSD"),
c.test = c(0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5),
d.zsd = c("ZAD", "ZSD", NA, NA, "ZSD", NA, "ZSD"),
d.test = c(1, 0, 0.5, 0.5, 0, 0, 1))
appendMin <- function(df, last_min = TRUE){
# select .zsd columns
zsd_cols <- grep(".zsd", names(df), value = TRUE)
zsd_df <- df[, zsd_cols]
if(last_min) { zsd_df <- rev(zsd_df) } # for last min
# select .test columns
test_cols <- gsub("zsd", "test",zsd_cols)
test_df <- df[, test_cols]
if(last_min) { test_df <- rev(test_df) } # for last min
# convert "Not Achieved ZSD" to "ZSD"
zsd_df[zsd_df == "Not Achieved ZSD" ] <- "ZSD"
# assign NA to non "ZSD" cells
zsd_df[zsd_df != "ZSD" ] <- NA
# assign 999 test_df values whose corresponding zsd_df is NA
test_df[is.na(zsd_df)] <- 999
# return cols which hold the first minimum
nams <- names(test_df)[apply(test_df, 1 ,which.min)]
# scrub .test suffix
nams <- gsub(".test", "", nams)
# return mins
mins <- apply(test_df, 1 ,min)
# assign values less than 999 as smallest test, or zero
df$smallest.test <- ifelse(mins < 999, mins, 0)
# assign name if corresponding min less than 999 or NA
df$zsd_level <- ifelse(mins < 999, nams, NA)
return(df)
}
ties_first <- appendMin(df, last_min = FALSE)
ties_last <- appendMin(df, last_min = TRUE)