dplyr 0.8.1 - Githubissues

As part of checking this package against the development version of dplyr, soon to become dplyr 0.8.1, I have noticed this failure;:
[master*] 408.5 MiB ❯ revdep_details(revdep = "healthcareai")
══ Reverse dependency check ════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════ healthcareai 2.3.0 ══

Status: BROKEN

── Newly failing

✖ checking examples ... ERROR

── Before ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
0 errors ✔ | 0 warnings ✔ | 0 notes ✔

── After ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
❯ checking examples ... ERROR
  Running examples in ‘healthcareai-Ex.R’ failed
  The error most likely occurred in:

  > ### Name: explore
  > ### Title: Explore a model's "reasoning" via counterfactual predictions
  > ### Aliases: explore
  > 
  > ### ** Examples
  > 
  > # First, we need a model on which to make counterfactual predictions
  > set.seed(5176)
  > m <- machine_learn(pima_diabetes, patient_id, outcome = diabetes,
  +                    tune = FALSE, models = "xgb")
  Training new data prep recipe...

  Variable(s) ignored in prep_data won't be used to tune models: patient_id

  diabetes looks categorical, so training classification algorithms.

  After data processing, models are being trained on 12 features with 768 observations.
  Based on n_folds = 5 and hyperparameter settings, the following number of models will be trained: 5 xgb's 

  Training at fixed values: eXtreme Gradient Boosting

1 error ✖ | 0 warnings ✔ | 0 notes ✔
I have not looked at it in details yet.
HealthCatalyst / healthcareai-r

dplyr 0.8.1 #1285
