Running examples in ‘timetk-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: step_slidify
> ### Title: Slidify Rolling Window Transformation
> ### Aliases: step_slidify tidy.step_slidify
> ### Keywords: datagen
> 
> ### ** Examples
> 
> library(recipes)
Loading required package: 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


Attaching package: ‘recipes’

The following object is masked from ‘package:stats’:

    step

> library(tidyverse)
── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
✔ ggplot2 3.4.0     ✔ purrr   0.3.5
✔ tibble  3.1.8     ✔ stringr 1.4.1
✔ tidyr   1.2.1     ✔ forcats 0.5.2
✔ readr   2.1.3     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter()  masks stats::filter()
✖ stringr::fixed() masks recipes::fixed()
✖ dplyr::lag()     masks stats::lag()
> library(tidyquant)
Loading required package: lubridate
Loading required package: timechange

Attaching package: ‘lubridate’

The following objects are masked from ‘package:base’:

    date, intersect, setdiff, union

Loading required package: PerformanceAnalytics
Loading required package: xts
Loading required package: zoo

Attaching package: ‘zoo’

The following objects are masked from ‘package:base’:

    as.Date, as.Date.numeric


Attaching package: ‘xts’

The following objects are masked from ‘package:dplyr’:

    first, last


Attaching package: ‘PerformanceAnalytics’

The following object is masked from ‘package:graphics’:

    legend

Loading required package: quantmod
Loading required package: TTR
> library(timetk)
> 
> # Training Data
> FB_tbl <- FANG %>%
+     filter(symbol == "FB") %>%
+     select(symbol, date, adjusted)
> 
> # New Data - Make some fake new data next 90 time stamps
> new_data <- FB_tbl %>%
+     tail(90) %>%
+     mutate(date = date %>% tk_make_future_timeseries(length_out = 90))
> 
> # OVERWRITE EXISTING COLUMNS -----
> 
> # Create a recipe object with a step_slidify
> rec_ma_50 <- recipe(adjusted ~ ., data = FB_tbl) %>%
+     step_slidify(adjusted, period = 50, .f = ~ AVERAGE(.x))
> 
> # Bake the recipe object - Applies the Moving Average Transformation
> training_data_baked <- bake(prep(rec_ma_50), FB_tbl)
Error in `prep()`:
! The selected variables should be numeric
Backtrace:
    ▆
 1. ├─recipes::bake(prep(rec_ma_50), FB_tbl)
 2. ├─recipes::prep(rec_ma_50)
 3. └─recipes:::prep.recipe(rec_ma_50)
 4.   ├─recipes::prep(x$steps[[i]], training = training, info = x$term_info)
 5.   └─timetk:::prep.step_slidify(x$steps[[i]], training = training, info = x$term_info)
 6.     └─rlang::abort("The selected variables should be numeric")
Execution halted