I am trying to obtain the weighted mean of some soil properties, weighted by their surface but aggregated by their owner and other levels. My dataset looks like this full_dataset and i would like to obtain the mean like thismean_dataset. My code right now is:
results<- original_df %>%
group_by(owner,cultivar) %>%
summarise(across(.cols= where(is.numeric),fns= weighted.mean(.,w= surface)))
but at the moment is not working, because the output as the same number of rows of the original dataset. What am I missing?
data:
structure(list(town = c("a", "a", "a", "a", "b", "b", "b", "b",
"b", "C", "C", "C", "C", "C", "C"), cultivar = c(1L, 1L, 2L,
2L, 1L, 2L, 3L, 4L, 4L, 3L, 3L, 2L, 2L, 1L, 1L), owner = c("A",
"A", "B", "C", "A", "B", "B", "C", "C", "B", "B", "C", "C", "A",
"A"), surface = c(456L, 446L, 462L, 120L, 204L, 250L, 642L, 466L,
580L, 258L, 146L, 617L, 79L, 304L, 48L), x1 = c(202L, 647L, 525L,
536L, 563L, 269L, 376L, 492L, 229L, 177L, 413L, 156L, 77L, 79L,
609L), x2 = c(91L, 334L, 110L, 533L, 161L, 605L, 344L, 380L,
221L, 368L, 179L, 531L, 357L, 66L, 157L), x3 = c(300L, 90L, 570L,
43L, 403L, 245L, 640L, 344L, 371L, 70L, 546L, 400L, 255L, 176L,
336L)), class = "data.frame", row.names = c(NA, -15L))
CodePudding user response:
If we use .
, we need the lambda (~
) i..e. the ~
is equivalent to function(.)
.
library(dplyr)
original_df %>%
group_by(owner,cultivar) %>%
dplyr::summarise(across(.cols= starts_with('x'),
~ weighted.mean(.,w= surface)), .groups = 'drop')
This may also work by just removing the ()
and the .
as the w
is already specified as 'surface' and thus it implicitly take the x
column looped
original_df %>%
group_by(owner,cultivar) %>%
dplyr::summarise(across(.cols= starts_with('x'),
weighted.mean, w= surface), .groups = 'drop')
-output
# A tibble: 5 × 5
owner cultivar x1 x2 x3
<chr> <int> <dbl> <dbl> <dbl>
1 A 1 376. 172. 226.
2 B 2 435. 284. 456.
3 B 3 332. 327. 486.
4 C 2 204. 514. 333.
5 C 4 346. 292. 359.