newdata

Introduction

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 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"

Reference Value

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:

• logical vectors are FALSE;
• double vectors are the mean;
• integer, Date, POSIXct and hms vectors are the floored mean;
• character vectors are the most common value or the first when sorted of the most common values;
• factor and ordered vectors are the first level.

The reference value of a variable can be modified with xnew_value(), which passes additional arguments to new_value().

xnew_data(old_data, xnew_value(dbl, .obs_only=TRUE))
#> # 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 4.5 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03"

Sequences

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:

• logical vectors are length 2 (TRUE and FALSE);
• double vectors are 30 equally spaced values from the minimum value to the maximum value;
• integer, Date, POSIXct and hms vectors are up to 30 discrete values from the minimum to the maximum value as evenly spaced as possible;
• character vectors are the number of unique values;
• factor and ordered vectors are the number of levels.

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.

1. The length of Date, POSIXct and hms sequences are controlled by 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"

Observed Values

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"

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 the observed combinations use xobs_only().

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 Variables

Modifying an existing variable or adding a new one is simple.

xnew_data(old_data, dbl= median(dbl, na.rm=TRUE), extra= c(TRUE, FALSE))
#> # A tibble: 2 × 10#> lgl int dbl chr fct ord dte dtt hms #> <lgl> <int> <dbl> <chr> <fct> <ord> <date> <dttm> <time>#> 1 FALSE 3 4.5 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03"#> 2 FALSE 3 4.5 most not obs a rarity 1970-01-04 1969-12-31 16:00:03 00'03"#> # ℹ 1 more variable: extra <lgl>

A modified or new variable takes the class of the values provided.

Casting Variables

New values can be cast to the class of the original variable with xcast().

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"

A Simple Wrapper

new_data() is a superseded wrapper on xnew_data() that is provided for consistency with existing code. It takes the variables to vary as a character vector and the length of all the sequences as a count.

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"

Installation

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"))

Contribution

Please report any issues.

Pull requests are always welcome.

Code of Conduct

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.