slide_dbl() and rollmean() returning NA instead of mean

Question

Calculating the rolling average, I have tried the following:

mutate(mean10min = slide_dbl('Cleaned BPM', mean, na.rm = TRUE, .before = 3, .after = 0, .complete = TRUE))

and

mutate(rolling_avg = rollmean('Cleaned BPM', k=3, fill=NA, align='right'))

However in both cases, the new column is filled with only NAs. My data is numeric. What is the issue and how do I solve it?

The data is part of a larger dataset, imported by read_excel(). Here's the relevant extract:

I have tried rolling_avg() on simple data, and there it works, thus there must be something wrong with the format of my 'Cleaned BPM', I assume.

Answer 1

Cleaned BPM requires backticks:

(See here re non-syntactic names.)

library(slider)
library(tidyverse)


# Backticks needed for non-syntactic names
tibble(`Cleaned BPM` = 1:100) |> 
  mutate(mean10min = slide_dbl(`Cleaned BPM`, mean, na.rm = TRUE, .before = 3, .after = 0, .complete = TRUE))
#> # A tibble: 100 × 2
#>    `Cleaned BPM` mean10min
#>            <int>     <dbl>
#>  1             1      NA  
#>  2             2      NA  
#>  3             3      NA  
#>  4             4       2.5
#>  5             5       3.5
#>  6             6       4.5
#>  7             7       5.5
#>  8             8       6.5
#>  9             9       7.5
#> 10            10       8.5
#> # ℹ 90 more rows


# Or clean the names first
library(janitor)

tibble(`Cleaned BPM` = 1:100) |> 
  clean_names() |> 
  mutate(mean10min = slide_dbl(cleaned_bpm, mean, na.rm = TRUE, .before = 3, .after = 0, .complete = TRUE))
#> # A tibble: 100 × 2
#>    cleaned_bpm mean10min
#>          <int>     <dbl>
#>  1           1      NA  
#>  2           2      NA  
#>  3           3      NA  
#>  4           4       2.5
#>  5           5       3.5
#>  6           6       4.5
#>  7           7       5.5
#>  8           8       6.5
#>  9           9       7.5
#> 10          10       8.5
#> # ℹ 90 more rows

^{Created on 2024-03-12 with reprex v2.1.0}