Description Usage Arguments Details Value Examples
Unlike summary()
, the tally functions return counts of individual
types of side effects. This makes them easy to use with
dplyr::summarise()
.
1 2 3 4 5 6 7 8 9 | tally_results(x)
tally_errors(x)
tally_warnings(x)
tally_messages(x)
tally_output(x)
|
x |
A “safely_mapped |
Importantly, the tally functions tell you how many elements returned a type of side effect, not how many side effects were returned. Some list elements might return more than one warning, for example, and these are not counted separately.
An integer vector of length 1.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | library(tibble)
library(dplyr)
library(tidyr)
library(collateral)
list("a", 10, 100) %>% map_safely(log) %>% tally_errors()
list(5, -12, 103) %>% map_quietly(log) %>% tally_warnings()
# if you're working with list-columns, the tally functions are useful
# in conjunction with dplyr::summarise()
mtcars %>%
rownames_to_column(var = "car") %>%
as_tibble() %>%
select(car, cyl, disp, wt) %>%
# spike some rows in cyl == 4 to make them fail
mutate(wt = dplyr::case_when(
wt < 2 ~ -wt,
TRUE ~ wt)) %>%
# nest and do some operations quietly()
nest(data = -cyl) %>%
mutate(qlog = map_quietly(data, ~ log(.$wt))) %>%
summarise(
num_results = tally_results(qlog),
num_warnings = tally_warnings(qlog))
|
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