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Current period year-to-date compared to previous period year-to-date

yoytd.Rd

  • This calculates the annual cumulative sum of targeted value and compares it with the previous period's annual cumulative to date sum using a standard or 5-5-4 calendar respecting any groups that are passed through with dplyr::group_by()

  • Use calculate to return the results

Usage

yoytd(.data, .date, .value, calendar_type, lag_n)

Arguments

.data

tibble or dbi object (either grouped or ungrouped)

.date

the date column to group by

.value

the value column to summarize

calendar_type

select either 'standard' or '5-5-4' calendar, see 'Details' for additional information

lag_n

the number of periods to lag

Value

ti object

Details

  • This function creates a complete calendar object that fills in any missing days, weeks, months, quarters, or years

  • If you provide a grouped object with dplyr::group_by(), it will generate a complete calendar for each group

  • The function creates a ti object, which pre-processes the data and arguments for further downstream functions

standard calendar

  • The standard calendar splits the year into 12 months (with 28–31 days each) and uses a 7-day week

  • It automatically accounts for leap years every four years to match the Gregorian calendar

5-5-4 calendar

  • The 5-5-4 calendar divides the fiscal year into 52 weeks (occasionally 53), organizing each quarter into two 5-week periods and one 4-week period.

  • This system is commonly used in retail and financial reporting

See also

Other time_intelligence: atd(), dod(), mom(), momtd(), mtd(), mtdopm(), pmtd(), pqtd(), pwtd(), pytd(), qoq(), qoqtd(), qtd(), qtdopq(), wow(), wowtd(), wtd(), wtdopw(), yoy(), ytd(), ytdopy()

Examples

yoytd(sales,.date=order_date,.value=quantity,calendar_type="standard",lag_n=1)
#> 
#> ── Year-to-date over previous year-to-date ─────────────────────────────────────
#> Function: `yoytd` was executed
#> 
#> ── Description: ──
#> 
#> This creates a daily `cumsum()` of the previous year quantity and compares it
#> with the daily `cumsum()` current year quantity from the start of the standard
#> calendar year to the end of the year
#> 
#> ── Calendar: ──
#> 
#> • The calendar aggregated order_date to the day time unit
#> • A standard calendar is created with 0 groups
#> • Calendar ranges from 2021-05-18 to 2024-04-20
#> • 222 days were missing and replaced with 0
#> • New date column date and year was created from order_date
#> 
#> ── Actions: ──
#> 
#> Error in str_detect(x@action@value[[1]], "32m"): could not find function "str_detect"