Reputation: 21440
I have a dataframe with columns of type list:
h1 h2 h3
1 6, 5.25 66, 4.2 4, 4.2
2 5, 11 7, 10 7, 10
3 6, 11 16, 11 16, 11
4 6, 0.25 7, 2.50 7, 7.77
I want to multiply the first value in each column with the second value, so in h1
this would be 6*5.25
, 5*11
, 6*11
, etc.
I've tried this code in dplyr
but it gives an error:
library(dplyr)
df0 %>%
mutate(across(c(everything()),
~ as.numeric(.x)[1]*12 + as.numeric(x.)[2]))
Error: Problem with `mutate()` input `..1`.
x 'list' object cannot be coerced to type 'double'
ℹ Input `..1` is `(function (.cols = everything(), .fns = NULL, ..., .names = NULL) ...`.
Reproducible data:
structure(list(h1 = list(c("6", "5.25"), c("5", "11"), c("6",
"11"), c("6", "0.25")), h2 = list(c("66", "4.2"), c("7", "10"
), c("16", "11"), c("7", "2.50")), h3 = list(c("4", "4.2"), c("7",
"10"), c("16", "11"), c("7", "7.77"))), class = "data.frame", row.names = c(NA,
-4L))
Upvotes: 2
Views: 101
Reputation: 40171
One solution might be:
df %>%
mutate(across(everything(), ~ map_dbl(., function(y) reduce(as.numeric(y), `*`))))
h1 h2 h3
1 31.5 277.2 16.80
2 55.0 70.0 70.00
3 66.0 176.0 176.00
4 1.5 17.5 54.39
To multiple the first element with a constant:
df %>%
mutate(across(everything(), ~ map_dbl(., function(y) reduce(as.numeric(y) * c(12, 1), `*`))))
Upvotes: 1
Reputation: 389325
You can use -
library(dplyr)
library(purrr)
df %>%
mutate(across(.fns = function(x) map_dbl(x, ~prod(as.numeric(.)))))
# h1 h2 h3
#1 31.5 277.2 16.80
#2 55.0 70.0 70.00
#3 66.0 176.0 176.00
#4 1.5 17.5 54.39
In base R, you can combine lapply
and sapply
-
df[] <- lapply(df, function(x) sapply(x, function(y) prod(as.numeric(y))))
Upvotes: 1