Aggregate multiple timeseries columns to a single one

The first column datetime will be kept.

Usage

aggregate_timeseries(df, varname, omit = NULL)

Arguments

df

data.frame or tibble, first column of name datetime being of class datetime and rest of columns being numeric

varname

character, name of the aggregation column

omit

character, name of columns to not aggregate

Value

tibble

Examples

# Example data set with 2 identical building profiles
df <- dplyr::select(
  energy_profiles, datetime, building1 = building, building2 = building
)
head(df)
#> # A tibble: 6 × 3
#>   datetime            building1 building2
#>   <dttm>                  <dbl>     <dbl>
#> 1 2023-01-01 00:00:00      2.61      2.61
#> 2 2023-01-01 00:15:00      2.42      2.42
#> 3 2023-01-01 00:30:00      2.23      2.23
#> 4 2023-01-01 00:45:00      2.04      2.04
#> 5 2023-01-01 01:00:00      1.85      1.85
#> 6 2023-01-01 01:15:00      1.78      1.78

# Aggregate the total building demand
head(aggregate_timeseries(df, varname = "total_buildings"))
#> # A tibble: 6 × 2
#>   datetime            total_buildings
#>   <dttm>                        <dbl>
#> 1 2023-01-01 00:00:00            5.23
#> 2 2023-01-01 00:15:00            4.85
#> 3 2023-01-01 00:30:00            4.47
#> 4 2023-01-01 00:45:00            4.09
#> 5 2023-01-01 01:00:00            3.71
#> 6 2023-01-01 01:15:00            3.56