I have two large tables (~12k x 6) based on a survey administered to children and their parent. The tables are identical in dimensions, types/classes, and were processed into R identically. After some wrangling (again, done same for children and parents) I run the following code:
UPDATE: It turns out the source of my issue is variable C which only has values 0 and 1 in the Children data set. Is there any way to get around this error when using summarise with table?
Parents %>%
summarise(across(A, ~ table(.x)),
across(B, ~table(.x)),
across(C, ~ table(.x)),
across(D, ~ table(.x)),
across(E, ~ table(.x)))
Children %>%
summarise(across(A, ~ table(.x)),
across(B, ~table(.x)),
across(C, ~ table(.x)),
across(D, ~ table(.x)),
across(E, ~ table(.x)))
For Parents I get the following output (frequency of unique values D var (1,2,3), others (0,1,2):
A B C D E
1 11840 11835 11409 11363 519
2 35 42 436 473 4912
3 3 1 33 42 6447
For Children I get the following error:
Error: Problem with `summarise()` input `..5`.
x Input `..5` must be size 4 or 1, not 3.
ℹ An earlier column had size 4.
ℹ Input `..5` is `(function (.cols = everything(), .fns = NULL, ..., .names = NULL) ...`.
Run `rlang::last_error()` to see where the error occurred.
Running rlang::last_error() returns:
<error/dplyr_error>
Problem with `summarise()` input `..5`.
x Input `..5` must be size 4 or 1, not 3.
ℹ An earlier column had size 4.
ℹ Input `..5` is `(function (.cols = everything(), .fns = NULL, ..., .names = NULL) ...`.
Backtrace:
Run `rlang::last_trace()` to see the full context.
Running rlang::last_trace() returns:
<error/dplyr_error>
Problem with `summarise()` input `..5`.
x Input `..5` must be size 4 or 1, not 3.
ℹ An earlier column had size 4.
ℹ Input `..5` is `(function (.cols = everything(), .fns = NULL, ..., .names = NULL) ...`.
Backtrace:
█
1. ├─`%>%`(...)
2. ├─dplyr::summarise(...)
3. ├─dplyr:::summarise.data.frame(...)
4. │ └─dplyr:::summarise_cols(.data, ...)
5. │ └─base::withCallingHandlers(...)
6. ├─dplyr:::abort_glue(...)
7. │ ├─rlang::exec(abort, class = class, !!!data)
8. │ └─(function (message = NULL, class = NULL, ..., trace = NULL, parent = NULL, ...
9. │ └─rlang:::signal_abort(cnd)
10. │ └─base::signalCondition(cnd)
11. └─(function (e) ...
Does anyone have any idea what might be happening?
For sanity sake, here are the str summaries:
> str(Parents)
'data.frame': 11878 obs. of 6 variables:
$ ID : chr "Parent 1" "Parent 2" "Parent 3" "Parent 4" ...
$ A : num 0 0 0 0 0 0 0 0 0 0 ...
$ B : num 0 0 0 0 0 0 0 0 0 0 ...
$ C : num 0 0 0 0 0 0 0 0 0 0 ...
$ D : num 2 2 1 2 3 3 2 3 3 2 ...
$ E : num 0 0 0 0 0 0 0 0 0 0 ...
> str(Children)
'data.frame': 11878 obs. of 6 variables:
$ ID : chr "Child 1" "Child 2" "Child 3" "Child 4" ...
$ A : num 0 0 0 0 0 0 0 0 0 0 ...
$ B : num 0 0 0 0 0 0 0 0 0 0 ...
$ C : num 0 0 0 0 0 0 0 0 0 0 ...
$ D : num 2 2 1 2 3 3 2 3 3 2 ...
$ E : num 0 0 0 0 0 0 0 0 0 0 ...
table will not necessarily fit in tidyverse pipeline always since it returns unequal number of values. I think it would be better to get the data in long format and use count. You'll get the same information but in long format.
library(dplyr)
library(tidyr)
Parents %>% pivot_longer(cols = A:E) %>% count(name, value)
The same should work for Children data.