Tsibble: Group hourly data on weekly basis, summarise them, calculate average and display and display seasonal data using gg_season() with period = "day"

[rcepka]

The base dataset - "pedestrian" from the tsibble package:

  pedestrian
#> # A tsibble: 66,037 x 5 [1h] <Australia/Melbourne>
#> # Key:       Sensor [4]
#>    Sensor         Date_Time           Date        Time Count
#>    <chr>          <dttm>              <date>     <int> <int>
#>  1 Birrarung Marr 2015-01-01 00:00:00 2015-01-01     0  1630
#>  2 Birrarung Marr 2015-01-01 01:00:00 2015-01-01     1   826
#>  3 Birrarung Marr 2015-01-01 02:00:00 2015-01-01     2   567
#>  4 Birrarung Marr 2015-01-01 03:00:00 2015-01-01     3   264
#>  5 Birrarung Marr 2015-01-01 04:00:00 2015-01-01     4   139
#>  6 Birrarung Marr 2015-01-01 05:00:00 2015-01-01     5    77
#>  7 Birrarung Marr 2015-01-01 06:00:00 2015-01-01     6    44
#>  8 Birrarung Marr 2015-01-01 07:00:00 2015-01-01     7    56
#>  9 Birrarung Marr 2015-01-01 08:00:00 2015-01-01     8   113
#> 10 Birrarung Marr 2015-01-01 09:00:00 2015-01-01     9   166
#> # ℹ 66,027 more rows

^{Created on 2024-08-20 with reprex v2.1.0}

I want to calculate the hourly average of pedestrians (column Count) on weekly basis ; - the average number of pedestrians for each week in hour 0, 1, 2, etc... The result should be plotted by gg_season() with flag period = "day"

I am able to do the summary and calculate the average like this:

  df <- pedestrian %>%     
    # Just simplifying data
    filter(lubridate::year(Date) == 2015 & Sensor == "Bourke Street Mall (North)") %>%    
    fill_gaps() %>%    
    group_by(Time) %>%     
    index_by(yrweek = yearweek(Date_Time)) %>%     
    summarise(avg = mean(Count)) %>%    
    arrange(yrweek, Time) 
  
  df
#> # A tsibble: 1,105 x 3 [1W]
#> # Key:       Time [25]
#>     Time   yrweek   avg
#>    <int>   <week> <dbl>
#>  1     0 2015 W08 419. 
#>  2     1 2015 W08 351  
#>  3     2 2015 W08 192  
#>  4     3 2015 W08 150. 
#>  5     4 2015 W08 106. 
#>  6     5 2015 W08  82  
#>  7     6 2015 W08  94.2
#>  8     7 2015 W08 240. 
#>  9     8 2015 W08 566. 
#> 10     9 2015 W08 756. 
#> # ℹ 1,095 more rows

^{Created on 2024-08-20 with reprex v2.1.0}

In next step want to plot the hourly average data for weeks like this:

df %>% gg_season(avg, period = "day")

I guess I need to change the "yrweek" column to add there also the hours.
How to achieve this please?
Thanks...