Previous period year-to-date

• For each group, pytd() will create the running annual sum of a value based on the calendar type for the previous year compared to the current year calendar date

• If no period exists, it will return NA

• The function returns a ti object which prints out the summary of steps and actions that will take to create the calendar table and calculations

• Use calculate to return the results

Usage

pytd(.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(), qoq(), qoqtd(), qtd(), qtdopq(), wow(), wowtd(), wtd(), wtdopw(), yoy(), yoytd(), ytd(), ytdopy()

Examples

pytd(sales,.date=order_date,.value=quantity,calendar_type="standard",lag_n=1)
#> 
#> ── Previous year-to-date ───────────────────────────────────────────────────────
#> Function: `pytd` was executed
#> 
#> ── Description: ──
#> 
#> This creates a daily `cumsum()` of the previous 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"