summarise() in dplyr 1.0.2 acting like mutate() - r

Question

Given a tibble that lists users, products, and product features, I am attempting to calculate the fraction of distinct product users who have a certain product feature:
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
df <- tribble(
~users, ~product, ~feature,
"bob","iPhone","screen",
"bob","iPhone","camera",
"bob","iPhone","facial recognition",
"sally","Android","screen",
"sally","Android","camera",
"sally","Android","facial recognition",
"joe","Huawei","screen",
"joe","Huawei","camera",
"joe","Huawei","facial recognition",
"rachel","iPhone","screen",
"rachel","iPhone","camera",
"rachel","iPhone","fingerprint sensor"
)
# Get count of distinct users by product
df <- df %>%
group_by(product) %>%
mutate(n_users = n_distinct(users)) %>%
ungroup()
df
#> # A tibble: 12 x 4
#> users product feature n_users
#> <chr> <chr> <chr> <int>
#> 1 bob iPhone screen 2
#> 2 bob iPhone camera 2
#> 3 bob iPhone facial recognition 2
#> 4 sally Android screen 1
#> 5 sally Android camera 1
#> 6 sally Android facial recognition 1
#> 7 joe Huawei screen 1
#> 8 joe Huawei camera 1
#> 9 joe Huawei facial recognition 1
#> 10 rachel iPhone screen 2
#> 11 rachel iPhone camera 2
#> 12 rachel iPhone fingerprint sensor 2
# Count the fraction of distinct users with given product feature
df <- df %>%
group_by(product, feature) %>%
summarise(feature_fraction = n()/n_users,
.groups = "drop_last")
df
#> # A tibble: 12 x 3
#> # Groups: product [3]
#> product feature feature_fraction
#> <chr> <chr> <dbl>
#> 1 Android camera 1
#> 2 Android facial recognition 1
#> 3 Android screen 1
#> 4 Huawei camera 1
#> 5 Huawei facial recognition 1
#> 6 Huawei screen 1
#> 7 iPhone camera 1
#> 8 iPhone camera 1
#> 9 iPhone facial recognition 0.5
#> 10 iPhone fingerprint sensor 0.5
#> 11 iPhone screen 1
#> 12 iPhone screen 1
Created on 2020-10-23 by the reprex package (v0.3.0)
devtools::session_info()
#> - Session info ---------------------------------------------------------------
#> setting value
#> version R version 4.0.2 (2020-06-22)
#> os Windows 10 x64
#> system x86_64, mingw32
#> ui RTerm
#> language (EN)
#> collate English_United States.1252
#> ctype English_United States.1252
#> tz America/New_York
#> date 2020-10-23
#>
#> - Packages -------------------------------------------------------------------
#> package * version date lib source
#> assertthat 0.2.1 2019-03-21 [1] CRAN (R 4.0.2)
#> backports 1.1.10 2020-09-15 [1] CRAN (R 4.0.2)
#> callr 3.4.4 2020-09-07 [1] CRAN (R 4.0.2)
#> cli 2.0.2 2020-02-28 [1] CRAN (R 4.0.2)
#> crayon 1.3.4 2017-09-16 [1] CRAN (R 4.0.2)
#> desc 1.2.0 2018-05-01 [1] CRAN (R 4.0.2)
#> devtools 2.3.1 2020-07-21 [1] CRAN (R 4.0.2)
#> digest 0.6.25 2020-02-23 [1] CRAN (R 4.0.2)
#> dplyr * 1.0.2 2020-08-18 [1] CRAN (R 4.0.2)
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#> evaluate 0.14 2019-05-28 [1] CRAN (R 4.0.2)
#> fansi 0.4.1 2020-01-08 [1] CRAN (R 4.0.2)
#> fs 1.5.0 2020-07-31 [1] CRAN (R 4.0.2)
#> generics 0.0.2 2018-11-29 [1] CRAN (R 4.0.2)
#> glue 1.4.2 2020-08-27 [1] CRAN (R 4.0.2)
#> highr 0.8 2019-03-20 [1] CRAN (R 4.0.2)
#> htmltools 0.5.0 2020-06-16 [1] CRAN (R 4.0.2)
#> knitr 1.29 2020-06-23 [1] CRAN (R 4.0.2)
#> lifecycle 0.2.0 2020-03-06 [1] CRAN (R 4.0.2)
#> magrittr 1.5 2014-11-22 [1] CRAN (R 4.0.2)
#> memoise 1.1.0 2017-04-21 [1] CRAN (R 4.0.2)
#> pillar 1.4.6 2020-07-10 [1] CRAN (R 4.0.2)
#> pkgbuild 1.1.0 2020-07-13 [1] CRAN (R 4.0.2)
#> pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.0.2)
#> pkgload 1.1.0 2020-05-29 [1] CRAN (R 4.0.2)
#> prettyunits 1.1.1 2020-01-24 [1] CRAN (R 4.0.2)
#> processx 3.4.4 2020-09-03 [1] CRAN (R 4.0.2)
#> ps 1.3.4 2020-08-11 [1] CRAN (R 4.0.2)
#> purrr 0.3.4 2020-04-17 [1] CRAN (R 4.0.2)
#> R6 2.4.1 2019-11-12 [1] CRAN (R 4.0.2)
#> remotes 2.2.0 2020-07-21 [1] CRAN (R 4.0.2)
#> rlang 0.4.7 2020-07-09 [1] CRAN (R 4.0.2)
#> rmarkdown 2.3 2020-06-18 [1] CRAN (R 4.0.2)
#> rprojroot 1.3-2 2018-01-03 [1] CRAN (R 4.0.2)
#> sessioninfo 1.1.1 2018-11-05 [1] CRAN (R 4.0.2)
#> stringi 1.5.3 2020-09-09 [1] CRAN (R 4.0.2)
#> stringr 1.4.0 2019-02-10 [1] CRAN (R 4.0.2)
#> testthat 2.3.2 2020-03-02 [1] CRAN (R 4.0.2)
#> tibble 3.0.3 2020-07-10 [1] CRAN (R 4.0.2)
#> tidyselect 1.1.0 2020-05-11 [1] CRAN (R 4.0.2)
#> usethis 1.6.1 2020-04-29 [1] CRAN (R 4.0.2)
#> utf8 1.1.4 2018-05-24 [1] CRAN (R 4.0.2)
#> vctrs 0.3.4 2020-08-29 [1] CRAN (R 4.0.2)
#> withr 2.3.0 2020-09-22 [1] CRAN (R 4.0.2)
#> xfun 0.16 2020-07-24 [1] CRAN (R 4.0.2)
#> yaml 2.2.1 2020-02-01 [1] CRAN (R 4.0.2)
As can be seen, the final tibble has multiple rows for group-key pairs with the same summary value. This is, to my knowledge, unexpected behavior for summarise and seems almost the same as what mutate would return. Given this open github issue, it appears that maybe all the kinks haven't been ironed out of the new version of summarise. I also could just be being stupid, and would appreciate if someone could help get me back on track!

Answer 1

The problem is your have multiple values for n_users for each group. The latest version of dplyr allow you to return more than one row per group if your summary function returns multiple values.
If you want to assume all the values for n_users will be the same per group, then you can do
df %>%
group_by(product, feature) %>%
summarise(feature_fraction = n()/first(n_users),
.groups = "drop_last")
That will make sure only one value is returned per group