identify_datefreq {vivainsights}

Identify date frequency based on a series of dates

Description

Takes a vector of dates and identify whether the frequency is 'daily', 'weekly', or 'monthly'. The primary use case for this function is to provide an accurate description of the query type used and for raising errors should a wrong date grouping be used in the data input.

Usage

identify_datefreq(x)

Arguments

x

Vector containing a series of dates.

Details

Date frequency detection works as follows:

• If at least three days of the week are present (e.g., Monday, Wednesday, Thursday) in the series, then the series is classified as 'daily'

• If the total number of months in the series is equal to the length, then the series is classified as 'monthly'

• If the total number of sundays in the series is equal to the length of the series, then the series is classified as 'weekly

Value

String describing the detected date frequency, i.e.:

• 'daily'

• 'weekly'

• 'monthly'

Limitations

One of the assumptions made behind the classification is that weeks are denoted with Sundays, hence the count of sundays to measure the number of weeks. In this case, weeks where a Sunday is missing would result in an 'unable to classify' error.

Another assumption made is that dates are evenly distributed, i.e. that the gap between dates are equal. If dates are unevenly distributed, e.g. only two days of the week are available for a given week, then the algorithm will fail to identify the frequency as 'daily'.

Examples

start_date <- as.Date("2022/06/26")
end_date <- as.Date("2022/11/27")

# Daily
day_seq <-
  seq.Date(
    from = start_date,
    to = end_date,
    by = "day"
  )

identify_datefreq(day_seq)

# Weekly
week_seq <-
  seq.Date(
    from = start_date,
    to = end_date,
    by = "week"
  )

identify_datefreq(week_seq)

# Monthly
month_seq <-
  seq.Date(
    from = start_date,
    to = end_date,
    by = "month"
  )
identify_datefreq(month_seq)