Previous: exporting data
A common task in the market research world is to collapse two or more categories together to see how the collapsed categories compare to one another. For example, if you asked people to rate their preference on a scale of 1 to 10, you might want to see how the people who provide a rating between 1 and 5 compare to those who rated it between 6 and 10. This goes by a number of names, including “Top Box” or “Nets”, depending on the use case. In Crunch, we call this family of features Subtotals. This vignette shows how to define, manage, and analyze variables with subtotals.
Subtotals can be applied to any Categorical or Categorical Array variable. In R, we can view and set subtotal definitions with the
subtotals() function. If there are no subtotals, the function will return
To add subtotals, we can assign a list of
Subtotal objects. Each
Subtotal object has three things: a
name to identify it; a set of
categories to pool together, referenced either by category name or id; and a location to show it, either
after a given category or with
"bottom" to pin it first or last in the list.
subtotals(ds$q1) <- list( Subtotal( name = "Mammals", categories = c("Cat", "Dog"), after = "Dog" ),Subtotal( name = "Can speak on command", categories = c("Dog", "Bird"), after = "Bird" ))
Now, if we check
subtotals(), we can see that we have saved them. In this output we see a few different aspects of subtotals: the
anchor is the id of the category to put the subtotal after (matching the
position argument in
Subtotal()), name, aggregation functions and
args, which in the this case are the category ids to include in the subtotal.
## anchor name func args kwargs ## 1 2 Mammals subtotal 1 and 2 positive: 1 and 2 | ## 2 3 Can speak on command subtotal 2 and 3 positive: 2 and 3 |
This shows up in the Categorical variable card on the web app like this:
Crunch also supports “Subtotal Differences” (sometimes also called “Net Promoter Scores”). The
negative argument of
Subtotal specifies which categories to subtract.
subtotals(ds$like_dogs) <- list( Subtotal( name = "Love minus Dislike & Hate", categories = c("Love"), negative = c("Dislike", "Hate"), position = "top" ))
Multiple Response variables can also have subtotals. To specify, use the alias or name of the subvariables as the categories.
subtotals(ds$allpets) <- list( Subtotal( name = "Any mammal", c("allpets_1", "allpets_2"), position = "top" ))
Subtotals and headings can be removed by assigning a
subtotals(ds$like_dogs) <- NULL
Sometimes there are a number of questions that have the same response categories. If the category names (or ids, if we’re using those) are the same, we can use the same set of subtotals across multiple variables.
<- list( pet_type_subtotals Subtotal( name = "Love minus Dislike & Hate", categories = c("Love"), negative = c("Dislike", "Hate"), position = "top" ))
subtotals(ds$like_dogs) <- pet_type_subtotals subtotals(ds$like_cats) <- pet_type_subtotals
Notice here, because each of the categories for these variables has slightly different ids, the
args in the output differs slightly. But, because we used category names when we were constructing our list of subtotals, when we store them on the variable itself, Crunch does the right thing and converts them over to the correct ids.
## anchor name func args kwargs ## 1 top Love minus Dislike & Hate subtotal 1 positive: 1 | negative: 4 and 5
## anchor name func args kwargs ## 1 top Love minus Dislike & Hate subtotal 5 positive: 5 | negative: 2 and 1
Now that we have defined subtotals on the congressional approval question, if we use it in a crosstab, we can see the subtotals.
crtabs(~like_dogs, data = ds)
## ## ## Love minus Dislike & Hate 0 ## Love 4 ## Like 4 ## Neutral 8 ## Dislike 2 ## Hate 2
We can even get just the subtotals as an array from the result if we want to ignore the constituent groups:
subtotalArray(crtabs(~like_dogs, data = ds))
## Love minus Dislike & Hate ## 0
If you don’t want to see the subtotals as part of these summaries, you can suppress them from display with the
noTransforms() function around
noTransforms(crtabs(~like_dogs, data = ds))
## like_dogs ## Love Like Neutral Dislike Hate ## 4 4 8 2 2
This does not modify the variable—the subtotals are still defined and visible in the web app—but they are removed from the current analysis.
Headings and Summary Statics are supported only by rcrunch and cannot be sent to the server. Therefore, they are only useful when working on
cube objects that you’ve already requested. The
addSummaryStat functions help you make these kinds of insertions.
# addSummaryStat is a convenient way to add mean/median addSummaryStat(crtabs(~q1, ds), margin = 1)
## ## ## Cat 6 ## Dog 4 ## Mammals 10 ## Bird 3 ## Can speak on command 7 ## mean 1.76923076923077
<- crtabs(~q1, data = ds) cube transforms(cube)$q1$insertions <- list(Heading("Mammals", position = "top"), Heading("Other", after = "Dog")) cube
## ## ## Mammals ## Cat 6 ## Dog 4 ## Other ## Bird 3