Element Properties

For any element or group, press the circle or square icon and select "Edit..." . This will bring up the Advanced Editor: The Element Properties editor uses a syntax called "JSON" (JavaScript Object Notation). The beauty is that you are seeing and editing the actual code that defines your Protobi project. The syntax is pretty simple, and you can figure it out pretty well from existing examples. The general pattern is `{"key":"value"}` pairs, separated by commas, where the key is always contained in quotes, and the value may be a string, number, null, an array in square brackets, or even another JSON object in curly braces. For reference, download the [Protobi JSON Syntax Cheat Sheet](images/tutorial/json-api/Protobi JSON Reference.pdf) in PDF. All of the above attributes have default values, and can be set to null or "". Below are the allowable values... ## Attributes ### `key` Each element has a unique `key` that identifies it. Multiple groups can refer to the same `key` as a child element, and each group will point to the same element with the same properties. By default, the key appears in the element's header. ### `displayKey` Specifies a different string to display in the element's header. This might be handy if the survey define a column with key **s0** but you would prefer the user to see **Specialty** instead. In this case you might have: ```json { "key": "s0", "displayKey": "Specialty" } ``` ### `title` (string) Longer text that appears below the element header. For instance, the element **specialty** might have the title ```json { "key": "s0", "displayKey": "Specialty", "title": "Doctor, what is your primary specialty?" } ``` ### `color` [heritable](#heritable) The color of the element icon. It may be any CSS named color (e.g. `"color": "gold"`) or hexadecimal color code (e.g.` "color": "#FA0"`) ```json { "key": "s0", "displayKey": "Specialty", "color": "#FA0", "color": "gold" } ``` ### `format` [heritable](#heritable) (object) Translates raw values to human-readable strings for display. Underlying value is unchanged. Formats are directly comparable to SPSS value labels. Formats are specified as objects with the raw value as the key and the formatted string as the value, e.g. ```json { "format": { "AD": "Andora", "AI": "Anguila", "AG": "Antigua", "AR": "Argentina", ... } } ``` If no format is defined, then all raw values that appear in the data are displayed directly in the distribution. If a format is defined, then all formatted values appear in the distribution, whether or not they have data values. Values that exist in the data but are not defined in the format will appear under "Other". You can toggle formatted value vs. raw value using the `Format` button. ### `display` Specify how the element should be displayed. Accepted values are: * "independent" * "checkbox" * "compact" ### `maxValue` (number) Reference value to calculate length of bars when numeric values are compacted to mean or median. ### `hidden` (boolean) hides the entire element! to unhide the element, use the listing of all elements on the left and click Shift-D ### `width` (number) Specify width in pixels. ### `height` (number) Specify height in pixels. ### `color` (string) Color code for element. Any CSS color string, such as "purple" or "#B69". ### `colors` ("ascending"|"descending"|object) Color scheme for element. A special value like `"descending"` or `"ascending"` indicates the values are ordinal and code from shades of blue to green. You can specify a hash of color codes for specific values, e.g. ```json { "1": "red", "2": "orange", "3": "yellow" } ``` ## Data ### `field` By default, Protobi assumes that each element key refers to a data column with the same name. For instance, the element with key `"s0"` will look for a data column `"s0"`. You can override this using the `field` attribute. For instance the following defines an element `"s0"` which looks to the data column `"spec"` for its data: ```json { "key": "s0", "field": "spec" } ``` ### `type` Specify the data type for the element. Accepted values are: * null * "" * "string" * "number" * "date" * "empty" If `"type"` is `"number"`, the default is to sort by value, show means and auto-bin into ranges. If `"type"` is `"number"`, the default is to sort by frequency, not show means, and show a search bar if more than 10 values. If `"type"` is `"date"`, Protobi parses the values as Date values. Protobi will recognize any date format recognized by the browser. If you have a special date format, you can set the dateFormat attribute. See the [Dates and times tutorial](/tutorial/dates) If `"type"` is `"empty"`, Protobi will not show data for this element at all. This is appropriate for groups of elements that have children but do not correspond to a data element themselves. If `"type"` is `""` or `null`, Protobi will make its best guess based on the available data. ### `dateFormat` (string) Specify a date format so that Protobi can parse the string values as dates. You can enter any format recognized [moment.js](https://momentjs.com/docs/#/parsing/string-format/), see this link for a complete syntax. For instance, if your date looks like "Monday April 9, 2018" you can specify "dateFormat": "dddd MMM D, YYYY" ### `split` (string|"word"|"letter") Specifies a delimiter to split each responses into an array of values. You can enter a specific delimiter, such as a comma (","), semicolon (";") or pipe ("|"). For instance, each response may be a list of the respondent's favorite pizza toppings separated by commas. ```json { "toppings": "s0", "split": "," } ``` You can also enter a special values like "word" which will intelligently break at all word and sentence boundaries, like spaces, periods, semicolons, and line breaks and drop some punctuation marks like "?" and "!". This is particularly useful when creating [Word clouds](/tutorial/word-cloud) Setting "split": "letter" will split the string into individual characters. Not that you would but you could. ### `roundby` (number|string|array) [heritable](#heritable) Specify bin size for grouping numeric values for analysis. Acceptable valuesa are: * 0 no binning at all * number specify linear bin size, e.g. 10 * array specify linear bin size, e.g. [1,5,10,25,50,100] * "auto" auto-guess bin size based on distribution * "log" logarithmic bins based on powers of 10 ### `weight` [heritable](#heritable) Specific a weight value for this element. Accepted values are: * String name of a data field with weight values, e.g. "sales" * String key of an element which calculates a weight, e.g. "s0" * Numeric constant to use as a weight, e.g. 1000 * Default indicating no weight null ### `denominator` (string) [heritable](#heritable) Divides response values by another data column or element. This is useful for transforming count responses into percentages. E.g.: ```json { "key": "s5a", "denominator": "s4" } ``` Note that when denominator is set, Protobi automatically calculates the mean as a ratio average rather than a simple average, see the [Ratios tutorial](/tutorial/ratios) ### `transform` (string) If the element is a group, standard transforms calculates a summary value from children: * "sum" returns sum of children * "mean" returns mean of children * "median" returns median of children * "min" returns minimum of children * "max" returns maximum of children * "stdev" returns standard deviation of children * "squish" condenses multiple string values a single multi-value response * "compact" transforms multiple binary elements into a single multi-value response There are a number of additional transforms for Date values (i.e. "type": "date"): * "minute" returns value to nearest minute * "hour" returns value to nearest hour * "day" returns value to nearest day * "month" returns value to nearest month * "year" returns value to nearest year * "dayofweek" returns name of day * "monthofyear" returns name of month For groups, it is possible to "squish" responses from multiple columns into one multiple-response element. This is useful for questions like "List up to three reasons". It de-duplicates responses for each individual. It is also possible to insert arbitrary JS code. The transform defines a function which is passed two objects, `row` represents the data row, and `this` represents the element itself. For instance: ```json { "key": "x-sqrt", "transform": "return Math.sqrt(row.x)" } ``` ### `string` ("toLower"|"toUpper"|"titleCase"|"trim"|"deburr") Specify any [lodash.js](https://lodash.com/docs/4.17.10#toLower) string functions, including: * "toUpper" converts to upper case * "toLower" converts to lower case * "capitalize" converts first character to upper case and rest to lower case. * "deburr" converts to Latin characters and removes accent marks * "trim" removes leading and trailing spaces ### `reformat [heritable](#heritable) (object) An object mapping raw values to new values, `{ "raw": "new", ...}`. It works a lot like [format](###format) except it actually transforms the values before analysis, and you can appy `"format"` to the results. Reformat can be used to convert values like `99` into missing values: ```json { "reformat": { "99": "" } } ``` Conversely, reformats can be useful to zero-fill missing values, e.g. ```json { "reformat": { "": 0 } } ``` Reformats are also used to recode verbatim responses. For instance, if a survey elicits respondent sex as a text open-ends, values might e recoded as : ```json { "Man": "M", "Male": "M", "male": "M", "Female": "F", "female": "F", "Woman": "F" } ``` The raw value is on the left, and is always written as a string. The new value on the right can be a number, boolean, null or string value. Note that reformat is applied before format is applied and can be used in conjunction with other transformations. ### `ceiling` [heritable](#heritable) (number) Bounds the distribution to this value or smaller. Useful for [Winsorizing](/tutorials/extremes) data. ### `floor` [heritable](#heritable) (number) Bounds the distribution to this value or greater. Useful for [Winsorizing](/tutorials/extremes) data. ### `filter` [heritable](#heritable) (object) An query expression that filters out all other values. This is useful for including only valid responses. Filter objects operate on the entire row, so the field name has to be specified. Constraints are specified in MongoDB query syntax. A few examples: * {"QA5a": {"$in": [1,2,3,4,5]}} accepts rows where QA5a is in [1,2,3,4, 5] * {"QA5a": {"$nin": [-9, 98, 99]}} rejects rows wehre QA5a is -9, 98 or 99 * {"QS4": {"$gte":0, "$lt": 100}} accepts rows where QA5a is 0 up to 99 ## Statistics ### `showMean` (boolean) [heritable](#heritable) ### `showSum` (boolean) [heritable](#heritable) ### `showMedian` (boolean) [heritable](#heritable) ### `showBasis` (boolean) [heritable](#heritable) ### `showMin` (boolean) [heritable](#heritable) ### `showMax` (boolean) [heritable](#heritable) ### `denominator` (boolean) [heritable](#heritable) ## Groups ### `children` (array) list all sub-elements for the group. can use to create a shell for a new element. (advance use) ### `hideChildren` (boolean) When transform or compactto is used, children are usually hidden for display purpose. Use to hide/unhide children ### `compactto` (number|string|array|null) [heritable](#heritable) Control how group is summarized in compact form: * A specific value, e.g. 1 for a top-box percentage. * An array, e.g. [1,2] for a top-N box percentage. * "$mean" for a summary of means. * "$sum" for a summary of sums. * "$min" for a summary of sums. * "$max" for a summary of sums. * "$median" for a summary of sums. * null for no summary. `compactto` can also be specified for an independent element to display a single summarized value. ## Heritable Changes to heritable properties propagate down to child elements within a group (and to their children...) * [format](#format), * [reformat](#reformat), * [maxValue](#maxValue), * [color](#color), * [weight](#weight), * [showSum](#showSum), * [showMean](#showMean), * [showMedian](#showMedian), * [showMin](#showMin), * [showMax](#showMax), * [showBasis](#showBasis), * [denominator](#denominator)