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New tsibble data and append new observations to a tsibble

Source: R/new-data.R
new-data.Rd

[Stable]

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().

Usage

new_data(.data, n = 1L, ...)

# S3 method for class '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 observations

  • n < 0, past observations

...

Passed to individual S3 method.

keep_all

If TRUE keep 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     -0.657
#> 2 2017-01-02 a     -0.479
#> 3 2017-01-03 a      0.637
#> 4 2017-01-04 a     NA    
#> 5 2017-01-01 b     -0.670
#> 6 2017-01-02 b      1.32 
#> 7 2017-01-03 b      0.514
#> 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     -0.657
#>  2 2017-01-02 a     -0.479
#>  3 2017-01-03 a      0.637
#>  4 2017-01-04 a     NA    
#>  5 2017-01-05 a     NA    
#>  6 2017-01-01 b     -0.670
#>  7 2017-01-02 b      1.32 
#>  8 2017-01-03 b      0.514
#>  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     -0.657
#>  4 2017-01-02 a     -0.479
#>  5 2017-01-03 a      0.637
#>  6 2016-12-30 b     NA    
#>  7 2016-12-31 b     NA    
#>  8 2017-01-01 b     -0.670
#>  9 2017-01-02 b      1.32 
#> 10 2017-01-03 b      0.514