← Dashboards & charts

Visualizing multiple-choice answers

To visualize multiple-choice answers, you have two options in DataLion:

Option 1: One data column per possible category

  • Create one column per possible category in the data set (e.g. brand; coded 0/1).

  • Create an additional question in the codebook in which each codebook category (e.g. brand) is read from its respective data column (see the example below).

  • Alternatively, you can keep the automatically generated codebook without creating an additional question in it and work via the DataLion frontend instead. In the automatically generated codebook there is a separate question with two categories (1 = mentioned, 0 = not mentioned) for every data column, i.e. a separate question for every brand, for example. In the frontend, the individual questions are then dragged onto each other and combined (“merge”) via drag & drop. The categories for “not mentioned” can be deactivated via the interface.

Example

Data set:

In the data set there is one row per respondent and one column per possible category (here brand). The value “1” means that the brand was mentioned.

Data set with one column per brand

Brand A;Brand B;Brand C;Brand D;Brand E;Brand F;Brand G;Brand H;Brand I;Brand J;Brand J;Brand K;Brand L 1;1;1;1;1;;;1;1;1;;1;1 1;1;1;;1;;;;1;;;1;1 1;;1;;;1;;;1;;;;1 1;;1;;1;1;;;1;;;;1 1;1;1;;;1;;;1;;1;1;1 1;;;1;1;;;;1;;;;1 1;1;1;;;;1;;;1;;;1 1;1;1;;1;;1;1;1;;;;1 1;;1;;1;;1;;1;;;1;1 1;;1;;1;;1;1;1;;;;1

Codebook:

There is one codebook question with one category per brand. Each brand is read from its data column (see the codebook column “variable”). To query the mention, a “1” (= mentioned) is entered in the “value” column.

Codebook question with one category per brand

category_import_id;question_id;variable;value;short_description;description;cat;chart_type;settings;level_1 37;13;Brand A;;Brands;Brands;Frage;b-bar;; 38;13;Brand A;1;Brand A;Brand A;Auspr;b-bar;; 39;13;Brand B;1;Brand B;Brand B;Auspr;b-bar;; 40;13;Brand C;1;Brand C;Brand C;Auspr;b-bar;; 41;13;Brand D;1;Brand D;Brand D;Auspr;b-bar;; 42;13;Brand E;1;Brand E;Brand E;Auspr;b-bar;; 43;13;Brand F;1;Brand F;Brand F;Auspr;b-bar;; 44;13;Brand G;1;Brand G;Brand G;Auspr;b-bar;; 45;13;Brand H;1;Brand H;Brand H;Auspr;b-bar;; 46;13;Brand I;1;Brand I;Brand I;Auspr;b-bar;; 47;13;Brand J;1;Brand J;Brand J;Auspr;b-bar;;

Result:

Resulting bar chart of the multiple responses

Option 2: One data column per mention

  • Create one column in the data set for each mention (1st mention, 2nd mention, 3rd mention, …). The columns contain the categories mentioned (e.g. brand A = 1, brand B = 2, brand C = 3, …).

  • In the codebook you then create a question in which each category reads the category from several columns using an OR combination. For brand B = 2, for example, the query ({{Nennung1 = 2 OR Nennung2 = 2 OR Nennung3 = 2}}) would return how often brand B was among the first three mentions.