I am finding an issue with the impute_mean_all() function. It appears in prior R versions that it would work perfectly, but now it seems to be running into an error when I use a tibble containing character and numerical columns and attempt to coerce all NAs to the mean.
Could you please investigate this for me?
Thanks!
James
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
library(naniar)
library(VIM)
#> Loading required package: colorspace
#> Loading required package: grid
#> The legacy packages maptools, rgdal, and rgeos, underpinning the sp package,
#> which was just loaded, will retire in October 2023.
#> Please refer to R-spatial evolution reports for details, especially
#> https://r-spatial.org/r/2023/05/15/evolution4.html.
#> It may be desirable to make the sf package available;
#> package maintainers should consider adding sf to Suggests:.
#> The sp package is now running under evolution status 2
#> (status 2 uses the sf package in place of rgdal)
#> VIM is ready to use.
#> Suggestions and bug-reports can be submitted at: https://github.com/statistikat/VIM/issues
#>
#> Attaching package: 'VIM'
#> The following object is masked from 'package:datasets':
#>
#> sleep
food_meanreplace <- food %>%
bind_shadow(only_miss = TRUE) %>%
add_label_shadow() %>%
impute_mean_all()
#> Warning: There were 2 warnings in `mutate()`.
#> The first warning was:
#> ℹ In argument: `Country = (function (x) ...`.
#> Caused by warning in `mean.default()`:
#> ! argument is not numeric or logical: returning NA
#> ℹ Run `dplyr::last_dplyr_warnings()` to see the 1 remaining warning.
Created on 2023-08-06 with [reprex v2.0.2](https://reprex.tidyverse.org/)
Hi Nick,
Thanks for developing the package!
I am finding an issue with the impute_mean_all() function. It appears in prior R versions that it would work perfectly, but now it seems to be running into an error when I use a tibble containing character and numerical columns and attempt to coerce all NAs to the mean.
Could you please investigate this for me?
Thanks!
James