R: Invalid calendar dates

clock-invalid {clock} | R Documentation

## Invalid calendar dates

### Description

This family of functions is for working with invalid calendar dates.

Invalid dates represent dates made up of valid individual components, which taken as a whole don't represent valid calendar dates. For example, for `year_month_day()` the following component ranges are valid: `year: [-32767, 32767]`, `month: [1, 12]`, `day: [1, 31]`. However, the date `2019-02-31` doesn't exist even though it is made up of valid components. This is an example of an invalid date.

Invalid dates are allowed in clock, provided that they are eventually resolved by using `invalid_resolve()` or by manually resolving them through arithmetic or setter functions.

### Usage

    invalid_detect(x)

    invalid_any(x)

    invalid_count(x)

    invalid_remove(x)

    invalid_resolve(x, ..., invalid = NULL)

### Arguments

`x` | `[calendar]` A calendar vector.
`...` | These dots are for future extensions and must be empty.
`invalid` | `[character(1) / NULL]` One of the following invalid date resolution strategies: `"previous"`: The previous valid instant in time. `"previous-day"`: The previous valid day in time, keeping the time of day. `"next"`: The next valid instant in time. `"next-day"`: The next valid day in time, keeping the time of day. `"overflow"`: Overflow by the number of days that the input is invalid by. Time of day is dropped. `"overflow-day"`: Overflow by the number of days that the input is invalid by. Time of day is kept. `"NA"`: Replace invalid dates with `NA`. `"error"`: Error on invalid dates. Using either `"previous"` or `"next"` is generally recommended, as these two strategies maintain the relative ordering between elements of the input. If `NULL`, defaults to `"error"`. If `getOption("clock.strict")` is `TRUE`, `invalid` must be supplied and cannot be `NULL`. This is a convenient way to make production code robust to invalid dates.

### Details

Invalid dates must be resolved before converting them to a time point.

It is recommended to use `"previous"` or `"next"` for resolving invalid dates, as these ensure that relative ordering among `x` is maintained. This is a often a very important property to maintain when doing time series data analysis. See the examples for more information.

### Value

- `invalid_detect()`: Returns a logical vector detecting invalid dates.

- `invalid_any()`: Returns `TRUE` if any invalid dates are detected.

- `invalid_count()`: Returns a single integer containing the number of invalid dates.

- `invalid_remove()`: Returns `x` with invalid dates removed.

- `invalid_resolve()`: Returns `x` with invalid dates resolved using the `invalid` strategy.

### Examples

    # Invalid date
    x <- year_month_day(2019, 04, 30:31, c(3, 2), 30, 00)
    x

    invalid_detect(x)

    # Previous valid moment in time
    x_previous <- invalid_resolve(x, invalid = "previous")
    x_previous

    # Previous valid day, retaining time of day
    x_previous_day <- invalid_resolve(x, invalid = "previous-day")
    x_previous_day

    # Note that `"previous"` retains the relative ordering in `x`
    x[1] < x[2]
    x_previous[1] < x_previous[2]

    # But `"previous-day"` here does not!
    x_previous_day[1] < x_previous_day[2]

    # Remove invalid dates entirely
    invalid_remove(x)

    y <- year_quarter_day(2019, 1, 90:92)
    y

    # Overflow rolls forward by the number of days between `y` and the previous
    # valid date
    invalid_resolve(y, invalid = "overflow")

[Package clock version 0.6.0 Index]