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Scan a tsibble for implicit missing observations

Source: R/gaps.R
scan_gaps.Rd

Scan a tsibble for implicit missing observations

Usage

scan_gaps(.data, .full = FALSE, .start = NULL, .end = NULL)

Arguments

.data

A tsibble.

.full

  • FALSE inserts NA for each keyed unit within its own period.

  • TRUE fills NA over the entire time span of the data (a.k.a. fully balanced panel).

  • start() pad NA to the same starting point (i.e. min(<index>)) across units.

  • end() pad NA to the same ending point (i.e. max(<index>)) across units.

.start, .end

Set custom starting/ending time that allows to expand the existing time spans.

See also

Other implicit gaps handling: count_gaps(), fill_gaps(), has_gaps()

Examples

scan_gaps(pedestrian)
#> # A tsibble: 3,011 x 2 [1h] <Australia/Melbourne>
#> # Key:       Sensor [4]
#>    Sensor         Date_Time          
#>    <chr>          <dttm>             
#>  1 Birrarung Marr 2015-04-05 02:00:00
#>  2 Birrarung Marr 2015-05-07 00:00:00
#>  3 Birrarung Marr 2015-05-07 01:00:00
#>  4 Birrarung Marr 2015-05-07 02:00:00
#>  5 Birrarung Marr 2015-05-07 03:00:00
#>  6 Birrarung Marr 2015-05-07 04:00:00
#>  7 Birrarung Marr 2015-05-07 05:00:00
#>  8 Birrarung Marr 2015-05-07 06:00:00
#>  9 Birrarung Marr 2015-05-07 07:00:00
#> 10 Birrarung Marr 2015-05-07 08:00:00
#> # ℹ 3,001 more rows