Predicate

To test a data point in a filter transform or a test property in conditional encoding, a prediction definition of the following forms must be specified:

1. a Vega expression string, where datum can be used to refer to the current data object. For example, datum.b2 > 60 would test if the value in the field b2 for each data point is over 60.

2. one of the field predicates: equal, lt, lte, gt, gte, range, oneOf, or valid,

3. a selection predicate, which define the names of a selection hat the data point should belong to (or a logical composition of selections).

4. a logical composition of (1), (2), or (3).

Field Predicate

Test if a field in the data point satisfies certain conditions.

For a field predicate, a field must be provided along with one of the predicate properties: equal, lt (less than), lte (less than or equal), gt (greater than), gte(greater than or equal), range, or oneOf. Values of these operators can be primitive types (string, number, boolean) or a DateTime definition object to describe time. In addition, timeUnit can be provided to further transform a temporal field.

Field Equal Predicate

For example, to check if the car_color field’s value is equal to "red", we can use the following predicate:

{"field": "car_color", "equal": "red"}

Field Less Than Predicate

For example, to check if the height field’s value is less than 180, we can use the following predicate:

{"field": "height", "lt": 180}

Field Less Than or Equals Predicate

For example, to check if the Year field’s value is less than or equals to "2000", we can use the following predicate:

{"timeUnit": "year", "field": "Year", "lte": "2000"}

Field Greater Than Predicate

To check if the state field’s value is greater than "Arizona" by string comparison, we can use the following predicate: (Note: Standard Javascript string comparison is done, ie., “A” < “B”, but “B” < “a”)

{"field": "state", "gt": "Arizona"}

Field Greater Than or Equals Predicate

For example, to check if the height field’s value is greater than or equals to 0, we can use the following predicate:

{"field": "height", "gte": 0}

Field Range Predicate

Examples

• {"field": "x", "range": [0, 5]}} checks if the x field’s value is in range [0,5] (0 ≤ x ≤ 5)
• {"timeUnit": "year", "field": "date", "range": [2006, 2008] }} checks if the date’s value is between year 2006 and 2008
• {"field": "date", "range": [{"year": 2006, "month": "jan", "date": 1}, {"year": 2008, "month": "feb", "date": 20}] }} checks if the date‘svalue is between Jan 1, 2006 and Feb 20, 2008.

Field One-Of Predicate

For example, {"field": "car_color", "oneOf": ["red", "yellow"]}} checks if the car_color field’s value is "red" or "yellow"

Field Valid Predicate

For example, {"field": "car_color", "valid": true}} checks if the car_color field’s value is valid meaning it is both not null and notNaN.

Selection Predicate

For a selection predicate, a selection name must be provided.

For example, with {"selection": "brush"}}, only data values that fall within the selection named brush will remain in the dataset as shownbelow.

All selection composition can be used here as well. For instance, {"selection": {"and": ["alex", "morgan"]}}} filtersfor data values that are within both the alex and morgan selections.

When you use a selection filter to dynamically filter the data, scale domains may change, which can lead to jumping titles. To prevent this, you can fix the minExtent of the axis whose scale domain changes. For example, to set the minimum extent to 30, add {"axis": {"minExtent": 30}} to the corresponding encoding.

Predicate Composition

We can also use the logical composition operators (and, or, not) to combine predicates.

Examples

• {"and": [{"field": "height", "gt": 0}, {"field": "height", "lt": 180}]} checks if the field "height" is between 0 and 180.
• {"not": {"field": "x", "range": [0, 5]}}} checks if the x field’s value is not in range [0,5] (0 ≤ x ≤ 5).