Modulation of appending/overwriting standardized variables in standardize() not working

[strengejacke]

Related to #30

d <- iris[1:4, ]

## NOT WORKING
# this should only return the two standardized variables, including suffix
datawizard::standardise(d, select = c("Sepal.Length", "Sepal.Width"), append = FALSE, suffix = "_z")
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 1    1.2402159   1.3887301          1.4         0.2  setosa
#> 2    0.3382407  -0.9258201          1.4         0.2  setosa
#> 3   -0.5637345   0.0000000          1.3         0.2  setosa
#> 4   -1.0147221  -0.4629100          1.5         0.2  setosa

## working
# this should return the original data frame and column bound 
# the standardized variables, including suffix
datawizard::standardise(d, select = c("Sepal.Length", "Sepal.Width"), append = TRUE, suffix = "_z")
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species Sepal.Length_z
#> 1          5.1         3.5          1.4         0.2  setosa      1.2402159
#> 2          4.9         3.0          1.4         0.2  setosa      0.3382407
#> 3          4.7         3.2          1.3         0.2  setosa     -0.5637345
#> 4          4.6         3.1          1.5         0.2  setosa     -1.0147221
#>   Sepal.Width_z
#> 1     1.3887301
#> 2    -0.9258201
#> 3     0.0000000
#> 4    -0.4629100

## NOT WORKING
# this should only return the standardized variables, w/o suffix
datawizard::standardise(d, select = c("Sepal.Length", "Sepal.Width"), append = FALSE, suffix = NULL)
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 1    1.2402159   1.3887301          1.4         0.2  setosa
#> 2    0.3382407  -0.9258201          1.4         0.2  setosa
#> 3   -0.5637345   0.0000000          1.3         0.2  setosa
#> 4   -1.0147221  -0.4629100          1.5         0.2  setosa

## NOT WORKING
# this should return the original data frame and the the standardized variables
# *overwrite* the related variables
datawizard::standardise(d, select = c("Sepal.Length", "Sepal.Width"), append = TRUE, suffix = NULL)
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species Sepal.Length
#> 1    1.2402159   1.3887301          1.4         0.2  setosa          5.1
#> 2    0.3382407  -0.9258201          1.4         0.2  setosa          4.9
#> 3   -0.5637345   0.0000000          1.3         0.2  setosa          4.7
#> 4   -1.0147221  -0.4629100          1.5         0.2  setosa          4.6
#>   Sepal.Width
#> 1         3.5
#> 2         3.0
#> 3         3.2
#> 4         3.1

^{Created on 2021-11-04 by the reprex package (v2.0.1)}

[strengejacke]

@mattansb @DominiqueMakowski If we change anything here, we need to be explicit in setting arguments in our other packages where we call standardize() on data frames.

[strengejacke]

expected behaviour (from my point of view):

d <- iris[1:4, ]

# this should only return the two standardized variables, including suffix
sjmisc::std(d, Sepal.Length, Sepal.Width, append = FALSE, suffix = "_z")
#>   Sepal.Length_z Sepal.Width_z
#> 1      1.2402159     1.3887301
#> 2      0.3382407    -0.9258201
#> 3     -0.5637345     0.0000000
#> 4     -1.0147221    -0.4629100

# this should return the original data frame and column bound 
# the standardized variables, including suffix
sjmisc::std(d, Sepal.Length, Sepal.Width, append = TRUE, suffix = "_z")
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species Sepal.Length_z
#> 1          5.1         3.5          1.4         0.2  setosa      1.2402159
#> 2          4.9         3.0          1.4         0.2  setosa      0.3382407
#> 3          4.7         3.2          1.3         0.2  setosa     -0.5637345
#> 4          4.6         3.1          1.5         0.2  setosa     -1.0147221
#>   Sepal.Width_z
#> 1     1.3887301
#> 2    -0.9258201
#> 3     0.0000000
#> 4    -0.4629100

# this should only return the standardized variables, w/o suffix
sjmisc::std(d, Sepal.Length, Sepal.Width, append = FALSE, suffix = NULL)
#>   Sepal.Length Sepal.Width
#> 1    1.2402159   1.3887301
#> 2    0.3382407  -0.9258201
#> 3   -0.5637345   0.0000000
#> 4   -1.0147221  -0.4629100

# suffix = NULL doesn't work here, need "" to overwrite

# this should return the original data frame and the the standardized variables
# *overwrite* the related variables
sjmisc::std(d, Sepal.Length, Sepal.Width, append = TRUE, suffix = "")
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 1    1.2402159   1.3887301          1.4         0.2  setosa
#> 2    0.3382407  -0.9258201          1.4         0.2  setosa
#> 3   -0.5637345   0.0000000          1.3         0.2  setosa
#> 4   -1.0147221  -0.4629100          1.5         0.2  setosa

^{Created on 2021-11-04 by the reprex package (v2.0.1)}

[strengejacke]

We could reduce the functionality to either overwrite or append standardized variables, then we would need only suffix. If we want the above shown behaviour, we would need append as well. So we should first decide how flexible this function should/needs to be, and then we can decide on the choice of arguments.

[strengejacke]

See #32

[mattansb]

Not sure I follow - are we talking about dropping the append arg, and having the suffix arg control whether the std-cols are appended or not, but in any case non-std cols are always returned?

If so, that sounds fine to me.

[strengejacke]

We can have two options: either, drop append, and then we can either overwrite or append standardized variables (see #32). Or we keep append, and can then also include/drop the full data frame (see #31 (comment)).

[DominiqueMakowski]

Mmmh in this light I would say that we only keep append as an argument.

• append=FALSE (default): only keep standardized; no renaming
• append=T: original data kept, standardized added with a default suffix (_Std or _z or whatnot)
• append="_standardized", original data kept, std. added with the said suffix.

The only option not available out-of-the-box is to rename & replace, but it's fine i think since i hardly see a common usecase for that and that just standardizing and renaming in a different step is a minor added trouble.

[strengejacke]

Why append instead of suffix? How can be define the suffix then?

[DominiqueMakowski]

because append suggests that it will append the standardized data to the other data, which is the primary effect (the suffix is just a "side-effect")

[strengejacke]

Ah, you mean append = "<my suffix>" will use the suffix.

[DominiqueMakowski]

yep

[strengejacke]

d <- iris[1:4, ]

# overwrite
datawizard::standardise(d, select = c("Sepal.Length", "Sepal.Width"))
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 1    1.2402159   1.3887301          1.4         0.2  setosa
#> 2    0.3382407  -0.9258201          1.4         0.2  setosa
#> 3   -0.5637345   0.0000000          1.3         0.2  setosa
#> 4   -1.0147221  -0.4629100          1.5         0.2  setosa

# append
datawizard::standardise(d, select = c("Sepal.Length", "Sepal.Width"), append = TRUE)
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species Sepal.Length_z
#> 1          5.1         3.5          1.4         0.2  setosa      1.2402159
#> 2          4.9         3.0          1.4         0.2  setosa      0.3382407
#> 3          4.7         3.2          1.3         0.2  setosa     -0.5637345
#> 4          4.6         3.1          1.5         0.2  setosa     -1.0147221
#>   Sepal.Width_z
#> 1     1.3887301
#> 2    -0.9258201
#> 3     0.0000000
#> 4    -0.4629100

# append, suffix
datawizard::standardise(d, select = c("Sepal.Length", "Sepal.Width"), append = "_std")
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species Sepal.Length_std
#> 1          5.1         3.5          1.4         0.2  setosa        1.2402159
#> 2          4.9         3.0          1.4         0.2  setosa        0.3382407
#> 3          4.7         3.2          1.3         0.2  setosa       -0.5637345
#> 4          4.6         3.1          1.5         0.2  setosa       -1.0147221
#>   Sepal.Width_std
#> 1       1.3887301
#> 2      -0.9258201
#> 3       0.0000000
#> 4      -0.4629100

^{Created on 2021-11-04 by the reprex package (v2.0.1)}