![[Stable]](figures/lifecycle-stable.svg)
append_row(): add new rows to the start/end of a tsibble by filling a key-index
pair and NA for measured variables.
append_case() is an alias of append_row().
new_data(.data, n = 1L, ...)
# S3 method for tbl_ts
new_data(.data, n = 1L, keep_all = FALSE, ...)
append_row(.data, n = 1L, ...)Arguments
- .data
A
tbl_ts.- n
An integer indicates the number of key-index pair to append. If
n > 0, future observationsn < 0, past observations
- ...
Passed to individual S3 method.
- keep_all
If
TRUEkeep all the measured variables as well as index and key, otherwise only index and key.
Examples
new_data(pedestrian)
#> # A tsibble: 4 x 2 [1h] <Australia/Melbourne>
#> # Key: Sensor [4]
#> Sensor Date_Time
#> <chr> <dttm>
#> 1 Birrarung Marr 2017-01-01 00:00:00
#> 2 Bourke Street Mall (North) 2017-01-01 00:00:00
#> 3 QV Market-Elizabeth St (West) 2017-01-01 00:00:00
#> 4 Southern Cross Station 2017-01-01 00:00:00
new_data(pedestrian, keep_all = TRUE)
#> # A tsibble: 4 x 5 [1h] <Australia/Melbourne>
#> # Key: Sensor [4]
#> Sensor Date_Time Date Time Count
#> <chr> <dttm> <date> <int> <int>
#> 1 Birrarung Marr 2017-01-01 00:00:00 NA NA NA
#> 2 Bourke Street Mall (North) 2017-01-01 00:00:00 NA NA NA
#> 3 QV Market-Elizabeth St (West) 2017-01-01 00:00:00 NA NA NA
#> 4 Southern Cross Station 2017-01-01 00:00:00 NA NA NA
new_data(pedestrian, n = 3)
#> # A tsibble: 12 x 2 [1h] <Australia/Melbourne>
#> # Key: Sensor [4]
#> Sensor Date_Time
#> <chr> <dttm>
#> 1 Birrarung Marr 2017-01-01 00:00:00
#> 2 Birrarung Marr 2017-01-01 01:00:00
#> 3 Birrarung Marr 2017-01-01 02:00:00
#> 4 Bourke Street Mall (North) 2017-01-01 00:00:00
#> 5 Bourke Street Mall (North) 2017-01-01 01:00:00
#> 6 Bourke Street Mall (North) 2017-01-01 02:00:00
#> 7 QV Market-Elizabeth St (West) 2017-01-01 00:00:00
#> 8 QV Market-Elizabeth St (West) 2017-01-01 01:00:00
#> 9 QV Market-Elizabeth St (West) 2017-01-01 02:00:00
#> 10 Southern Cross Station 2017-01-01 00:00:00
#> 11 Southern Cross Station 2017-01-01 01:00:00
#> 12 Southern Cross Station 2017-01-01 02:00:00
new_data(pedestrian, n = -2)
#> # A tsibble: 8 x 2 [1h] <Australia/Melbourne>
#> # Key: Sensor [4]
#> Sensor Date_Time
#> <chr> <dttm>
#> 1 Birrarung Marr 2014-12-31 22:00:00
#> 2 Birrarung Marr 2014-12-31 23:00:00
#> 3 Bourke Street Mall (North) 2015-02-16 22:00:00
#> 4 Bourke Street Mall (North) 2015-02-16 23:00:00
#> 5 QV Market-Elizabeth St (West) 2014-12-31 22:00:00
#> 6 QV Market-Elizabeth St (West) 2014-12-31 23:00:00
#> 7 Southern Cross Station 2014-12-31 22:00:00
#> 8 Southern Cross Station 2014-12-31 23:00:00
tsbl <- tsibble(
date = rep(as.Date("2017-01-01") + 0:2, each = 2),
group = rep(letters[1:2], 3),
value = rnorm(6),
key = group
)
#> Using `date` as index variable.
append_row(tsbl)
#> # A tsibble: 8 x 3 [1D]
#> # Key: group [2]
#> date group value
#> <date> <chr> <dbl>
#> 1 2017-01-01 a -1.20
#> 2 2017-01-02 a 1.70
#> 3 2017-01-03 a 0.753
#> 4 2017-01-04 a NA
#> 5 2017-01-01 b -0.697
#> 6 2017-01-02 b 1.22
#> 7 2017-01-03 b -0.405
#> 8 2017-01-04 b NA
append_row(tsbl, n = 2)
#> # A tsibble: 10 x 3 [1D]
#> # Key: group [2]
#> date group value
#> <date> <chr> <dbl>
#> 1 2017-01-01 a -1.20
#> 2 2017-01-02 a 1.70
#> 3 2017-01-03 a 0.753
#> 4 2017-01-04 a NA
#> 5 2017-01-05 a NA
#> 6 2017-01-01 b -0.697
#> 7 2017-01-02 b 1.22
#> 8 2017-01-03 b -0.405
#> 9 2017-01-04 b NA
#> 10 2017-01-05 b NA
append_row(tsbl, n = -2)
#> # A tsibble: 10 x 3 [1D]
#> # Key: group [2]
#> date group value
#> <date> <chr> <dbl>
#> 1 2016-12-30 a NA
#> 2 2016-12-31 a NA
#> 3 2017-01-01 a -1.20
#> 4 2017-01-02 a 1.70
#> 5 2017-01-03 a 0.753
#> 6 2016-12-30 b NA
#> 7 2016-12-31 b NA
#> 8 2017-01-01 b -0.697
#> 9 2017-01-02 b 1.22
#> 10 2017-01-03 b -0.405