You can view the dependency graph of an output by right-clicking on it and selecting Dependency Graph from the context menu.

As an example, the dependency graph above is for the word cloud shown below. We can see from this dependency graph that the word cloud has been created using the variables Reasons for being a detractor: Bakery and Detractors: Bakery.

More information is in our help center article Viewing Dependency Graphs to Understand Calculations and Performance.

Show each row in a variable set or grid as separate tables:

When working with data in a variable set or grid format, you may want to see results for one variable at a time or calculate different values for the individual attributes. Below, I will show you how to split your variable set to show results for each variable.

Your table may look something like this:

To update the results to show multiple tables, take these steps:

1. In the Data Sets tree, select the variable set. If you plan to use the original variable set elsewhere in your project, first make a copy of the variable set by going to Home > Selection > Duplicate.
2. Go to Data Manipulation > Variables and click Split.
3. The variable set will now separate out into individual variables. Drag these new variables onto the Page to create separate tables:

Treat the data in your variable set as a scale and show the overall average for each row:

To get a table of averages, take these steps:

1. In the Data Sets tree, select the variable set. If you plan to use the original variable set elsewhere in your project, first make a copy of the variable set by going to Home > Selection > Duplicate.
2. From the Object Inspector, go to Properties > GENERAL > Structure change the drop-down to Numeric - Multi
3. Drag the variable set onto the Page

Calculate Top 2 (T2B) or Bottom 2 (B2B) Boxes, and show only those results in a table:

To calculate a Top 2 Box (Love and Like), take these steps:

1. In the Data Sets tree, select the variable set.
2. From the Object Inspector, go to Properties > TRANSFORMATIONS > Top 2 boxes.
3. Click the Fix button when the orange warning message appears in the object inspector.
4. Double-check that the items selected in the Count this Value column have been checked (adjust as required), then click OK.

5. Drag the new variable onto the page to create a table that includes only the Top 2 Box (Love and Like) results:

To create a Bottom 2 Box (Hate and Dislike):

1. In the Data Sets tree, select the variable set.
2. From the Object Inspector, go to Properties > TRANSFORMATIONS > Bottom 2 boxes.
3. Click the Fix button when the orange warning message appears in the object inspector.
4. Double-check that the items selected in the Count this Value column have been checked (adjust as required), then click OK.

5. Drag the new variable onto the page to create a table that includes only the Top 2 Box (Hate and Dislike) results:

Note that you can create Top K and Bottom K boxes, as well as Top 3 and Bottom 3 boxes, by selecting the appropriate items from Properties > TRANSFORMATIONS. When selecting Top K and Bottom K boxes, you have the ability to specify exactly how many categories should be included in the calculation.

The numeric data values of your variable will be used to assign the top and bottom categories when creating box scores. For example, if you have a flipped 5-point rating scale, where 1 = Love and 5 = Hate, Displayr will use the highest numeric values when assigning the Top box score (Dislike + Hate), and the lowest numeric values when assigning the Bottom box (Love + Like) score. Ensure that you are accounting for flipped scales when creating your box scores.

How do I create a new variable?

There are a number of ways to create new variables, including group variables into a variable set, creating a filter variable, creating custom variables, etc. For more information about which option is best suited for your project's needs, see 10 Ways to Create New Variables in Displayr

The NET does not add up to 100%

See the "Rebasing multiple-response data to the NET" section of Easy Functions for Automating Filters and Rebasing

How do I rebase one question based on another question?

See the "Rebasing questions based on other questions" section of Easy Functions for Automating Filters and Rebasing

How do I band a numeric variable into categories?

This can be done using drag-and-drop, R, or JavaScript. See How to Band Numeric Variables in Displayr for more information.

1. How do I find resources on filtering?

• Go to Learn More about Filtering in Displayr

2. My filter has become invalid

• If you receive a red QFilter error then this signifies that there is an issue with the filter applied to your output:
  
• You should find the filter under Data Sets, click it, and then update the condition where necessary.
  
• If the error is in a variable that your filter uses then it will indicate the invalid variable that requires fixing.
• If the issue has been resolved but the output still shows as invalid, untick and tick Automatic.

3. Applying a filter to a visualization produces a warning

• If you receive an orange warning like the below, this is because any filters should be applied to the source table rather than the visualization:
• It will not affect your results but ensure the source table has the correct filter applied.

4. Applying a filter to my output produces a 0 observations error

• If your table returns the below error but you expect there to be data, you should check the condition of the filter variable.
  
• Check the raw data via Insert > More > Tables > Raw Data by selecting the filter variable and the source variables used in the condition. This will allow you to see if the issue is the actual data or simply the filter.

5. Applying multiple filters to my output doesn’t produce the desired result

• Check the logic conditions in the individual filter variables.
• Check the raw data via Insert > More > Tables > Raw Data by selecting the filter variables and the source variables used in the condition.
• Check that the filter variables are grouped correctly. Non-grouped filters are treated as an AND condition whereas grouped filters are treated as an OR condition.
  • If your filters should be grouped (i.e. perform an OR condition), select them under Data Sets and go to Insert > Data Manipulation > Combine.
  • If your filters should not be grouped (i.e. perform an AND condition), select them under Data Sets and go to Insert > Data Manipulation > Split.

6. My R output doesn’t filter even though a filter is applied

• If you have an R output with custom code that does not reference QFilter and then apply a filter, you will get the following warning:
  
• QFilter is essentially a reference that stores the record-level TRUE/FALSE generated from the filter(s) selected under Input > FILTERS & WEIGHT > Filter(s). See Filters in Displayr for further details.
• If you are dealing with a single variable, adding [QFilter] to your R reference will then apply the filter(s) selected on your output:
  
• If you are dealing with multiple columns of data then [QFilter,, drop = FALSE] is more appropriate as the filter needs to specifically be applied to the rows while leaving the columns as is.

7. Unwanted filters are showing in View mode

• By default, all filters in your document are visible in your published dashboard. Any filters you don't want to show can be hidden via the Hidden except in the data tree option:
• Note that you cannot hide filters that are currently in use in an output. You must do this prior to applying the filters.
• It is possible, however, for Q users to open their Displayr document QPack and set the filters hidden in the Variables and Questions tab using the H in the Tags column. Please use the workflow outlined in How to Edit a Displayr Document in Q.

8. I've opened my Displayr document QPack in Q and it's asking me if I want to reset my filters

• While you can open Displayr documents in Q, filters that are created in Displayr work differently. In Displayr it is possible to group filters to allow you to join filter variables with OR. Q, by contrast, can only join filter variables with AND. If you select an output where such a filter exists, you should select No to maintain the current set up.
• See the Combining filters section of How to Filter Data in Displayr for more details.

9. I'm trying to create a filter using R code but it doesn't work

• Go to How to Use Basic R Code for Creating Filters

10. I have unwanted items in my control box list

• Items to be displayed come from both the Item list and Items from fields. By default, First option; Second option will appear under Item list but you can remove these. If you, therefore, have overlapping items listed between the two options, you will need to remove one of these duplicates:
  
• If you are only using the Items from option, you can Hide items from the referenced table or amend your R code accordingly.

11. My output(s) won't update when connected to my control box(es)

• Check Automatic is ticked on the output
• If you are using manipulation settings: Check the correct control box has been referenced under ROW/COLUMN MANIPULATIONS > Rows/Columns to show and Select rows to show by is set to Choosing from Combo Box or List Box control.
  
  Remember, if you have used the DATA MANIPULATION > Switch rows and columns option, you will need to apply these settings in the reverse manipulation menu.
• If you are using filters: Check that you have applied the correct filter to the output and ensure any source table is included on the same page.
• If you are using multiple filter variables, ensure they are all applied to your source outputs.
• Check that the filter condition references the correct control box name.
  
  If using a Page Master, you will need to first find the correct template via Appearance > Page Master. Remember if you copy all the outputs from one page to another, the reference names will be different.
• Check that the control box items match the source question being referenced. Remember that any merging of table categories for the source question will also need to be reflected in the control item list.
• Check that you are using the correct formula as single and multiple-response questions require different code. See How to Connect Filters to a Combo Box (Control) for further details.
• Below is an example of a single-response condition based on the categories from Age: 

Age %in% Combo.box

• And this is an example of a multiple-response condition based on the variables from Rolling months:

rowSums(`Rolling months`[, Combo.box, drop = FALSE]) > 0

• If you are using a filter variable that combines all the conditions, ensure they are all connected with the & (AND) symbol. For example:

Age %in% combo.box.age & Gender %in% combo.box.gender

• If you are using a single-response question as the basis of your control categories but have created overlapping NET categories, you will need to set this up instead as a set of binary variables. You can easily do this via Insert > Filter > Filters from Selected Data. You will then need to adjust the filter formula to reference these new filter variables.

12. I added a total sample item to my control box but my output(s) won't show total base

• Check the formula condition in your control filter variable. Filter variables need to return 1 or TRUE when selecting records and 0 or FALSE when not selecting them.
• The general way for setting a 'total sample' default among custom filter categories is by adding an if/else statement. Below is my existing filter condition:

usergroups %in% Combo.box.groups

• I also have an item in my combo box called Total Sample so I need to add that condition and wrap it all within an if/else statement. To do this I can use the rep function and reference the length of the id variable which signifies the number of records in the file. This will then generate a 1 for every record in the data set if this condition is TRUE, otherwise, it will return the second filter condition.

if ("Total Sample" %in% Combo.box.groups) {
rep(TRUE, length(id))
} else {
usergroups %in% Combo.box.groups
}

• If 'total sample' is instead based on another filter variable, check its logic condition.
• Check any applicable raw data via Insert > More > Tables > Raw Data by selecting the filter variable and the source variables used in the condition.

13. I've applied a filter in View mode but it is no longer applied when I go to another page

• View mode filters only apply to the current page. See Allowing Users to Filter Pages in Dashboards and Using Displayr to Filter Data, Analyses, and Whole Reports for further details.
• If you wish to apply global filters to your document, you have 2 choices:
  • Create one or more control boxes on a single page whereby every subsequent page has a filter applied that references these controls.
  • Add your control box(es) to a Page Master and ensure this layout is used on every page you wish to apply this filter. This will result in any control user selections on one of these pages being reflected in all the other pages using this layout. See How to Use the Same Control on Multiple Pages.

14. I'm trying to export reports with selected filters but my reports aren't filtering properly

• The Select multiple filters to export multiple reports option requires all underlying tables and outputs to be on visible pages. Any items on hidden pages will not be filtered. It works in the same way as applying page filters from the Filters drop-down menu in View mode.
• If you are using tables as the underlying data, you should place them on the same pages as your final outputs.
• If you are using R outputs as the underlying data, these also need to be filterable, that is, they need to reference QFilter in the code. Unless you are using a custom R output, this will already be included in the underlying R code.
• See How to Automatically Export Multiple Reports with Different Filters for further details.

15. I'm trying to display the sample size description but it won't show the filter label based on the control box

• When filtering data through a control box, you may wish to display the sample size description via Insert > More > Data > Sample Size Description. In this case, the underlying code behind the widget won't be able to deal with this by default. To customize your code, go to the Advanced Customization: Dynamic updating with Combo or List Boxes section of How to Customize the Sample Size Description Widget.

More often than not, a market research survey consists of at least one multiple-response question. A multi-response question allows respondents to give more than one answer. This type of question usually appears as a Binary - Multi or Binary - Grid, for example:

This blog post could have actually been titled "Help, my multiple response questions shows all 100%!" because this issue comes up fairly frequently for Displayr users.

What does a good Binary - Multi question look like?

For multiple response questions, separate variables for each category of the question are necessary to capture all the responses. These variables are coded as dichotomies, where each variable has two possible categories indicating whether a response was selected or not.

Let’s take the example above, where the question, "Which of the following drinks have you bought in the last week?" and provides four possible responses. The respondent can indicate multiple choices by checking a box next to each choice. The variables in the data should be structured as though the respondent was asked four individual questions:

There are a few ways that data providers code these types of questions. Ideally, multiple response questions should be marked as Multiple Response Sets in the SPSS file. If not, Displayr will try and guess whether or not the variables need to be combined into multiple response questions. Such guessing may be inaccurate and may require additional work to manipulate the data to the correct format.

How you should configure your Value Attributes?

Binary - Multi or Binary - Grid questions have a different Value Attributes window from other question types. There is a column called Count this Value which is used to indicate which response code should be counted in the table for a particular question, and there is no Value column, as the numeric values do not play a role for this kind of data. In Displayr, to get the Value Attributes dialog box you need to select the variable in the Data Sets window and in the Object Inspector on the right side of the screen click Properties > DATA VALUES > Values. You will see a window pop-up similar to below with two columns, one for Count this Value and Missing Values.

The Count this Value checkbox tells Displayr which responses are the affirmative ones or the ones that you want to count in your Counts (ns). By leaving BOTH boxes unchecked, you are including the response in your Sample Size (base n) but not counting it in your Counts (you should select this setting for your Unselected/No responses). The Missing Data checkbox tells Displayr which codes should be ignored from the question (and removed from the Sample Size). Ideally, respondents who were not asked a particular question or given a particular option, whether that was intentional or not, should use this checkbox.

Please note any changes will be made to whichever variables are selected. If you select only a subset of variables that make up a question, Displayr will give a warning in the Value Attributes dialog box telling you The current selection is part of a larger Variable Set. To edit the whole Variable Set instead, select the Variable Set in the Data Tree. If you do not select the Variable Set in the Data Tree the changes will only apply to the selected variable.

Different flavors of coding

The following examples show you what the Value Attributes should look like for the different scenarios.

Selected, not selected and missing data

The following Binary Multi question is by far the best way to set up a Binary Multi question.

The selections in the Count this Value column are the same as the previous case, indicating that we will count all respondents who answered Yes for each option. By leaving the No category unchecked for Count this Value and the drop-down under Missing Values specifying Include in analyses you will count the responses in the sample size but not in the counts.

The Missing data category is unticked in the Count this Value and the drop-down under Missing Values specifying Exclude from analyses, and this means that the base sample for each category will be all those respondents who do not have missing data. In this case, if you wanted to base the statistics on the total sample, you would need to select Include in analyses in the Missing Data column, and the Missing data category will then be treated just the same as the No category.

Selected and not selected codes, selected and missing

It is not appropriate to record missing values in a data file as 0. Why, because as stated above the No response is usually coded as a 0. If the same was for the missing values then it is impossible to determine which respondents said No and which respondents were not asked the question.  For example, if people are asked which brands they have consumed, but are only shown brands that they are aware of, then in this scenario it would be appropriate. You will need to confirm with your data provider or survey design as to whether or not there indeed should be another code marking those respondents who did not see an option/question. You may need to get an amended copy of your data with the new missing data code included.

The Value Attributes for this question has two possible response codes for each option: Yes and No or Missing and No. Therefore, the selections in the Count This Value column will indicate that when calculating the percentages and other statistics.

If your Binary Multi question only has two response codes, one must be ticked in the Count This Value column, and the other must be un-ticked. We only want to count people who said Yes for each response. Both values should be Include in analyses in the Missing Values column.

No to option and option or missing and option

Ideally, multiple-response variables should be coded as No is a 0, and Yes is a 1, alternatively Not selected is a 0 and Selected is a 1. However, sometimes the actual option label is used in the label of the code. This means that the selected multiple variables have different label attributes for each variable. The Value Attributes dialog box will warn you that there are Fundamentally Different Variables. By selecting Proceed Regardless, changes made will apply to all the selected variables, regardless of the actual meaning of the variables.

You can see that the Value Attributes are set up similarly to the selected and not selected variables above.

We need to tell Displayr which values to count, and which not to count or treat as missing data. This will apply to all the variables selected at the time.

There are other coding scenarios out there so if you need help figuring out how to configure your Value Attributes, please drop an email to support@displayr.com.