# Subtotals and Headings

    library(crunch)

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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.

# Getting and setting subtotals on a categorical variable

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 `NULL`:

    subtotals(ds$q1)

    ## NULL

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 `position="top"` or `"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 `after` or `position` argument in `Subtotal()`), name, aggregation functions and `args`, which in the this case are the category ids to include in the subtotal.

    subtotals(ds$q1)

    ##   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”122). 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"
        )
    )

# Subtotals on multiple response variables

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"
        )
    )

# Removing subtotals

Subtotals and headings can be removed by assigning a `NULL` value.

    subtotals(ds$like_dogs) <- NULL

# Setting many subtotals

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.

    pet_type_subtotals <- list(
        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.

    subtotals(ds$like_dogs)

    ##   anchor                      name     func args                          kwargs
    ## 1    top Love minus Dislike & Hate subtotal    1 positive: 1 | negative: 4 and 5

    subtotals(ds$like_cats)

    ##   anchor                      name     func args                          kwargs
    ## 1    top Love minus Dislike & Hate subtotal    5 positive: 5 | negative: 2 and 1

# Computing with subtotals

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 `crtabs()`.

    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.

# Other types of insertions

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 `Heading` and `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

    cube <- crtabs(~q1, data = ds)
    transforms(cube)$q1$insertions <- list(Heading("Mammals", position = "top"), Heading("Other", after = "Dog"))
    cube

    ##
    ##
    ## Mammals
    ##     Cat 6
    ##     Dog 4
    ##   Other
    ##    Bird 3

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