Fix: only call replace_na(., 0) on numeric columns

[DavisVaughan]

We are updating tidyr::replace_na() to utilize the vctrs package, and that results in slightly stricter / more correct type conversions. See tidyverse/tidyr#1219

We noticed in revdeps that this package broke. An easy way to see this is by installing the above mentioned PR and running:

library(wpa)

# Create a sample small dataset
orgs <- c("Customer Service", "Financial Planning", "Biz Dev")
em_data <- em_data[em_data$Organization %in% orgs, ]

# Return visualization of percentage distribution
workpatterns_area(em_data, return = "plot", values = "percent")
#> Error: Problem with `mutate()` column `PersonId`.
#> ℹ `PersonId = (structure(function (..., .x = ..1, .y = ..2, . = ..1) ...`.
#> x Can't convert `replace` <double> to match type of `data` <character>.

The problem boils down to the fact that you are calling mutate_all(df, ~replace_na(., 0)) on a df that has a mixture of character and numeric columns. Notably, PersonId and group are character columns, and you can no longer use a numeric 0 as a replacement value for these.

It seems like you probably just wanted to replace NAs in numeric columns, so this PR changes to a mutate() call that targets only numeric columns.

We would greatly appreciate if you could merge this PR and submit a patch release of your package to CRAN so we can send tidyr in!

[ghost]

All CLA requirements met.

[martinctc]

Thank you @DavisVaughan - will review this change soon as I can and push a new version to CRAN.

[martinctc]

@DavisVaughan - can confirm that these changes have been merged and pushed to CRAN, in v1.6.3. Thanks again