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I have this data frame,
set.seed(124)
id <- rnorm(5, mean = 100, sd = 59)
charVar <- c("Eeny (2), meeny (10), miny (21), moe (1)",
"Catch (112), a (2), tiger (33), by (44), the (2), toe (24)",
NA,
"If (2), he (33), hollers (15), let (66), him (1), go (55)",
"Eeny (224), meeny (44), miny (50), moe (76)")
df <- data.frame(id, charVar)
df
> df
id charVar
1 18.28083 Eeny (2), meeny (10), miny (21), moe (1)
2 102.26107 Catch (112), a (2), tiger (33), by (44), the (2), toe (24)
3 54.98122 <NA>
4 112.52606 If (2), he (33), hollers (15), let (66), him (1), go (55)
5 184.10674 Eeny (224), meeny (44), miny (50), moe (76)
I want to sort every element in the rows by the numbers with it. The expected output should look like this:
> df
id charVar
1 18.28083 miny (21), meeny (10), Eeny (2), moe (1)
2 102.26107 Catch (112), by (44), tiger (33), toe (24), a (2), the (2)
3 54.98122 <NA>
4 112.52606 let (66), go (55), he (33), hollers (15), If (2), him (1)
5 184.10674 Eeny (224), moe (76), miny (50), meeny (44)
Any idea how to achive the expected result? Any help would be greatly appreciated.
I have this data frame,
set.seed(124)
id <- rnorm(5, mean = 100, sd = 59)
charVar <- c("Eeny (2), meeny (10), miny (21), moe (1)",
"Catch (112), a (2), tiger (33), by (44), the (2), toe (24)",
NA,
"If (2), he (33), hollers (15), let (66), him (1), go (55)",
"Eeny (224), meeny (44), miny (50), moe (76)")
df <- data.frame(id, charVar)
df
> df
id charVar
1 18.28083 Eeny (2), meeny (10), miny (21), moe (1)
2 102.26107 Catch (112), a (2), tiger (33), by (44), the (2), toe (24)
3 54.98122 <NA>
4 112.52606 If (2), he (33), hollers (15), let (66), him (1), go (55)
5 184.10674 Eeny (224), meeny (44), miny (50), moe (76)
I want to sort every element in the rows by the numbers with it. The expected output should look like this:
> df
id charVar
1 18.28083 miny (21), meeny (10), Eeny (2), moe (1)
2 102.26107 Catch (112), by (44), tiger (33), toe (24), a (2), the (2)
3 54.98122 <NA>
4 112.52606 let (66), go (55), he (33), hollers (15), If (2), him (1)
5 184.10674 Eeny (224), moe (76), miny (50), meeny (44)
Any idea how to achive the expected result? Any help would be greatly appreciated.
Share Improve this question edited Feb 11 at 12:09 ThomasIsCoding 103k9 gold badges36 silver badges101 bronze badges asked Feb 4 at 10:11 JontroPothonJontroPothon 6004 silver badges10 bronze badges3 Answers
Reset to default 6Looks like this is a follow up to your previous question. Instead of dealing with XY problem, avoid the problem from the start:
#example data
df <- data.frame(var_1 = c(10, 5, 6, 0),
var_2 = c(0, 0, 3, 0),
var_3 = c(2, 0, 9, 0))
#sort and collapse to string
df$resString <- apply(df, 1, function(x, y = x[ x != 0 ]){
ix <- order(y, decreasing = TRUE)
if(length(ix)) paste(paste0(names(y)[ ix ], " (", y[ ix ], ")"), collapse = ", ") else return(NA)
})
#sort and keep as list column
df$resList <- apply(df[, grep("^var", colnames(df), value = TRUE) ], 1,
function(i) sort(i[ i != 0 ], decreasing = TRUE))
#df
# var_1 var_2 var_3 resString resList
# 1 10 0 2 var_1 (10), var_3 (2) 10, 2
# 2 5 0 0 var_1 (5) 5
# 3 6 3 9 var_3 (9), var_1 (6), var_2 (3) 9, 6, 3
# 4 0 0 0 <NA>
As you've tagged tidyverse and data.table here are approaches using both.
tidyverse approach
Essentially we strsplit() charVar into a list-column where each element is a character vector, tidyr::unnest() into long form, extract the numbers, then dplyr::summarise() back into one row per id, where we paste() back together the values in decreasing order():
library(dplyr)
df |>
mutate(charVar = strsplit(charVar, ", ")) |>
tidyr::unnest(charVar) |>
mutate(n = as.integer(gsub("\\D+", "", charVar))) |>
summarise(
charVar = paste(charVar[order(-n)], collapse = ", "),
.by = id
)
# id charVar
# 1 18.28083 miny (21), meeny (10), Eeny (2), moe (1)
# 2 102.26107 Catch (112), by (44), tiger (33), toe (24), a (2), the (2)
# 3 54.98122 NA
# 4 112.52606 let (66), go (55), he (33), hollers (15), If (2), him (1)
# 5 184.10674 Eeny (224), moe (76), miny (50), meeny (44)
data.table approach
There is no equivalent of tidyr::unnest(). While the same results can be achieved with unlisting, here's an approach which feels more idiomatic, which modifies charVar in place:
library(data.table)
setDT(df)
df[, charVar := lapply(charVar, \(x) {
parts <- unlist(strsplit(x, ", "))
n <- as.integer(gsub("\\D+", "", parts))
paste(parts[order(-n)], collapse = ", ")
})]
# id charVar
# <num> <list>
# 1: 18.28083 miny (21), meeny (10), Eeny (2), moe (1)
# 2: 102.26107 Catch (112), by (44), tiger (33), toe (24), a (2), the (2)
# 3: 54.98122 NA
# 4: 112.52606 let (66), go (55), he (33), hollers (15), If (2), him (1)
# 5: 184.10674 Eeny (224), moe (76), miny (50), meeny (44)
With base R, you can try
transform(
df,
charVar = sapply(
strsplit(charVar, ", "),
\(x) toString(x[order(-as.integer(gsub("\\D+", "", x)))])
)
)
or you can use gtools::mixedsort for simpler implementation
library(gtools)
df %>%
mutate(charVar = sapply(
strsplit(charVar, ", "),
\(x) toString(mixedsort(x, decreasing = TRUE))
))
which gives
id charVar
1 18.28083 miny (21), meeny (10), Eeny (2), moe (1)
2 102.26107 Catch (112), by (44), tiger (33), toe (24), a (2), the (2)
3 54.98122 NA
4 112.52606 let (66), go (55), he (33), hollers (15), If (2), him (1)
5 184.10674 Eeny (224), moe (76), miny (50), meeny (44)
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