My tsibble dataset contains hourly data, which I want to aggregate on weekly basis and compute a hourly summary for specified variable.
Then I would like to plot the data using gg_season(variable, period = "day")

Preparing the df:

  df <- pedestrian %>%     
    # Just simplifying data
    filter(lubridate::year(Date) == 2015 & Sensor == "Bourke Street Mall (North)") %>%    
    group_by(Time) %>%     
    index_by(yrweek = yearweek(Date_Time)) %>%     
    summarise(total = sum(Count)) %>%    
    arrange(yrweek, Time) 
  
  df
#> # A tsibble: 1,104 x 3 [1W]
#> # Key:       Time [24]
#>     Time   yrweek total
#>    <int>   <week> <int>
#>  1     0 2015 W08  2512
#>  2     1 2015 W08  2106
#>  3     2 2015 W08  1152
#>  4     3 2015 W08   899
#>  5     4 2015 W08   635
#>  6     5 2015 W08   492
#>  7     6 2015 W08   565
#>  8     7 2015 W08  1442
#>  9     8 2015 W08  3397
#> 10     9 2015 W08  4535
#> # ℹ 1,094 more rows

^{Created on 2024-08-19 with reprex v2.1.0}

Now I would like to plot the hourly data in this manner:
df %>% gg_season(total, period = "day")

Of course I cant, because the “yrweek” column in my df is not of hourly granularity.

How to tackle this please? How to convert the “yrweek” column to the format that it can be plotted using feasts::gg_season() function?

Many thanks in advance.