newdata is an R package to generate new data frames by varying some variables while holding the others constant.
By default, all specified variables vary across their range while all other variables are held constant at a reference value. The user can specify the length of each sequence, require that only observed values and combinations are used and add new variables. Types, classes, factor levels and time zones are always preserved.
Consider the following observed ‘old’ data frame.
library(newdata) newdata::old_data #> # A tibble: 3 × 9 #> lgl int dbl chr fct ord dte dtt hms #> <lgl> <int> <dbl> <chr> <fct> <ord> <date> <dttm> <time> #> 1 TRUE 1 1 most most most 1970-01-02 1969-12-31 16:00:01 00'01" #> 2 FALSE 4 4.5 most most most 1970-01-05 1969-12-31 16:00:04 00'04" #> 3 NA 6 8.2 a rarity a rari… a ra… 1970-01-07 1969-12-31 16:00:06 00'06"
By default all variables are set to a reference value.
xnew_data(old_data) #> # A tibble: 1 × 9 #> lgl int dbl chr fct ord dte dtt hms #> <lgl> <int> <dbl> <chr> <fct> <ord> <date> <dttm> <time> #> 1 FALSE 3 4.57 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03"
The reference value depends on the class of the variable, by default:
Specifying a variable causes it to vary sequentially across its range.
xnew_data(old_data, int) #> # A tibble: 6 × 9 #> lgl int dbl chr fct ord dte dtt hms #> <lgl> <int> <dbl> <chr> <fct> <ord> <date> <dttm> <time> #> 1 FALSE 1 4.57 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03" #> 2 FALSE 2 4.57 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03" #> 3 FALSE 3 4.57 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03" #> 4 FALSE 4 4.57 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03" #> 5 FALSE 5 4.57 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03" #> 6 FALSE 6 4.57 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03"
By default the sequence depends on the class of the variable:
These values can be overridden by setting the following options:
new_data.length_out_lgl, which is 2 by default, for logical vectors;new_data.length_out_dbl, which is 30 by default, for double vectors;new_data.length_out_int, which is 30 by default, for integer, Date, POSIXct and hms vectors^1;new_data.length_out_chr, which is Inf by default, for character, factor and ordered vectors.new_data.length_out_int as they are treated as integers for the purpose of generating a sequence.When programming it is strongly recommended that the user explicitly specify the length of each sequence individually.
xnew_data(old_data, lgl, xnew_seq(int, length_out = 3)) #> # A tibble: 6 × 9 #> lgl int dbl chr fct ord dte dtt hms #> <lgl> <int> <dbl> <chr> <fct> <ord> <date> <dttm> <time> #> 1 FALSE 1 4.57 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03" #> 2 FALSE 3 4.57 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03" #> 3 FALSE 6 4.57 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03" #> 4 TRUE 1 4.57 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03" #> 5 TRUE 3 4.57 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03" #> 6 TRUE 6 4.57 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03"
A third alternative is to specify the length of all the sequences in the data set but this can result in less common character strings or later factor or ordered levels being dropped.
xnew_data(old_data, dbl, int, .length_out = 2) #> # A tibble: 4 × 9 #> lgl int dbl chr fct ord dte dtt hms #> <lgl> <int> <dbl> <chr> <fct> <ord> <date> <dttm> <time> #> 1 FALSE 1 1 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03" #> 2 FALSE 6 1 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03" #> 3 FALSE 1 8.2 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03" #> 4 FALSE 6 8.2 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03"
The user can also indicate whether only observed values should be used in the sequence.
xnew_data(old_data, xnew_seq(int, length_out = 3, obs_only = TRUE)) #> # A tibble: 3 × 9 #> lgl int dbl chr fct ord dte dtt hms #> <lgl> <int> <dbl> <chr> <fct> <ord> <date> <dttm> <time> #> 1 FALSE 1 4.57 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03" #> 2 FALSE 4 4.57 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03" #> 3 FALSE 6 4.57 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03"
The xobs_only() function can be used to filter out unobserved values after the sequence has been generated.
xnew_data(old_data, xobs_only(xnew_seq(int, length_out = 3))) #> # A tibble: 2 × 9 #> lgl int dbl chr fct ord dte dtt hms #> <lgl> <int> <dbl> <chr> <fct> <ord> <date> <dttm> <time> #> 1 FALSE 1 4.57 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03" #> 2 FALSE 6 4.57 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03"
and when two or more variables are specified all combinations are used.
xnew_data(old_data, int, fct) #> # A tibble: 18 × 9 #> lgl int dbl chr fct ord dte dtt hms #> <lgl> <int> <dbl> <chr> <fct> <ord> <date> <dttm> <time> #> 1 FALSE 1 4.57 most not obs a rar… 1970-01-04 1969-12-31 16:00:03 00'03" #> 2 FALSE 1 4.57 most a rarity a rar… 1970-01-04 1969-12-31 16:00:03 00'03" #> 3 FALSE 1 4.57 most most a rar… 1970-01-04 1969-12-31 16:00:03 00'03" #> 4 FALSE 2 4.57 most not obs a rar… 1970-01-04 1969-12-31 16:00:03 00'03" #> 5 FALSE 2 4.57 most a rarity a rar… 1970-01-04 1969-12-31 16:00:03 00'03" #> 6 FALSE 2 4.57 most most a rar… 1970-01-04 1969-12-31 16:00:03 00'03" #> 7 FALSE 3 4.57 most not obs a rar… 1970-01-04 1969-12-31 16:00:03 00'03" #> 8 FALSE 3 4.57 most a rarity a rar… 1970-01-04 1969-12-31 16:00:03 00'03" #> 9 FALSE 3 4.57 most most a rar… 1970-01-04 1969-12-31 16:00:03 00'03" #> 10 FALSE 4 4.57 most not obs a rar… 1970-01-04 1969-12-31 16:00:03 00'03" #> 11 FALSE 4 4.57 most a rarity a rar… 1970-01-04 1969-12-31 16:00:03 00'03" #> 12 FALSE 4 4.57 most most a rar… 1970-01-04 1969-12-31 16:00:03 00'03" #> 13 FALSE 5 4.57 most not obs a rar… 1970-01-04 1969-12-31 16:00:03 00'03" #> 14 FALSE 5 4.57 most a rarity a rar… 1970-01-04 1969-12-31 16:00:03 00'03" #> 15 FALSE 5 4.57 most most a rar… 1970-01-04 1969-12-31 16:00:03 00'03" #> 16 FALSE 6 4.57 most not obs a rar… 1970-01-04 1969-12-31 16:00:03 00'03" #> 17 FALSE 6 4.57 most a rarity a rar… 1970-01-04 1969-12-31 16:00:03 00'03" #> 18 FALSE 6 4.57 most most a rar… 1970-01-04 1969-12-31 16:00:03 00'03"
to only get observed combinations.
xnew_data(old_data, xobs_only(int, fct)) #> # A tibble: 3 × 9 #> lgl int dbl chr fct ord dte dtt hms #> <lgl> <int> <dbl> <chr> <fct> <ord> <date> <dttm> <time> #> 1 FALSE 1 4.57 most most a rari… 1970-01-04 1969-12-31 16:00:03 00'03" #> 2 FALSE 4 4.57 most most a rari… 1970-01-04 1969-12-31 16:00:03 00'03" #> 3 FALSE 6 4.57 most a rarity a rari… 1970-01-04 1969-12-31 16:00:03 00'03"
Modifying an existing variable or changing an existing one is simple.
xnew_data(old_data, lgl = median(lgl, na.rm = TRUE), extra = c(TRUE, FALSE)) #> # A tibble: 2 × 10 #> lgl int dbl chr fct ord dte dtt hms #> <dbl> <int> <dbl> <chr> <fct> <ord> <date> <dttm> <time> #> 1 0.5 3 4.57 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03" #> 2 0.5 3 4.57 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03" #> # ℹ 1 more variable: extra <lgl>
Casting variables to be the same class as the original is achieved as follows.
xnew_data(old_data, xcast(lgl = 1, int = 7, dbl = 10L, fct = "a rarity", hms = "00:00:02")) #> # A tibble: 1 × 9 #> lgl int dbl chr fct ord dte dtt hms #> <lgl> <int> <dbl> <chr> <fct> <ord> <date> <dttm> <time> #> 1 TRUE 7 10 most a rarity a rari… 1970-01-04 1969-12-31 16:00:03 00'02"
Although superseded, for consistency with existing code new_data() which is a simple wrapper on xnew_data() allows the user to pass a character vector and to specifying the length of all the sequences is also provided.
new_data(old_data, seq = c("int", "fct"), length_out = 5)
#> # A tibble: 15 × 9
#> lgl int dbl chr fct ord dte dtt hms
#> <lgl> <int> <dbl> <chr> <fct> <ord> <date> <dttm> <time>
#> 1 FALSE 1 4.57 most not obs a rar… 1970-01-04 1969-12-31 16:00:03 00'03"
#> 2 FALSE 1 4.57 most a rarity a rar… 1970-01-04 1969-12-31 16:00:03 00'03"
#> 3 FALSE 1 4.57 most most a rar… 1970-01-04 1969-12-31 16:00:03 00'03"
#> 4 FALSE 2 4.57 most not obs a rar… 1970-01-04 1969-12-31 16:00:03 00'03"
#> 5 FALSE 2 4.57 most a rarity a rar… 1970-01-04 1969-12-31 16:00:03 00'03"
#> 6 FALSE 2 4.57 most most a rar… 1970-01-04 1969-12-31 16:00:03 00'03"
#> 7 FALSE 3 4.57 most not obs a rar… 1970-01-04 1969-12-31 16:00:03 00'03"
#> 8 FALSE 3 4.57 most a rarity a rar… 1970-01-04 1969-12-31 16:00:03 00'03"
#> 9 FALSE 3 4.57 most most a rar… 1970-01-04 1969-12-31 16:00:03 00'03"
#> 10 FALSE 4 4.57 most not obs a rar… 1970-01-04 1969-12-31 16:00:03 00'03"
#> 11 FALSE 4 4.57 most a rarity a rar… 1970-01-04 1969-12-31 16:00:03 00'03"
#> 12 FALSE 4 4.57 most most a rar… 1970-01-04 1969-12-31 16:00:03 00'03"
#> 13 FALSE 6 4.57 most not obs a rar… 1970-01-04 1969-12-31 16:00:03 00'03"
#> 14 FALSE 6 4.57 most a rarity a rar… 1970-01-04 1969-12-31 16:00:03 00'03"
#> 15 FALSE 6 4.57 most most a rar… 1970-01-04 1969-12-31 16:00:03 00'03"
To install the latest release version from CRAN.
install.packages("newdata")
To install the latest development version from GitHub
# install.packages("pak")
pak::pak("poissonconsulting/newdata")
or from r-universe.
install.packages("newdata", repos = c("https://poissonconsulting.r-universe.dev", "https://cloud.r-project.org"))
Please report any issues.
Pull requests are always welcome.
Please note that the newdata project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
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