isTypeNumber

Tests if the data type of the input value is a number and returns a Boolean true or false.

The similar isNumber function tests if a value can be parsed to a number, meaning it returns true for numbers and valid number/currency strings (e.g. '$100'). By contrast, isTypeNumber returns true if the data type of the input value is number.

The function may be used in conditionals — see below for an example.

Parameters

VALUE (any)
The value to test.

Examples

Assume a "Describe a JSON Object" project with this data:

{
   "data": {
      "mnth": "January",
      "year": "2023",
      "state": "California",
      "branches": [
         "Los Angeles",
         "San Francisco",
         "Oakland"
      ],
      "totalSales": 245687.89,
      "sales": [
         80678.50,
         91000.39,
         74000.00
        ],
      "target": 250000,
      "manager": {
         "name": "Robyn Banks",
         "age": 51, 
         "married": false
      }
   }
}

Here's how you might use isTypeNumber to check values in the data:

ATL in Text	Result	Notes
`[[isTypeNumber(WholeJSON.data.year)]]`	false	The test value is a string.
`[[isTypeNumber(WholeJSON.data.sales)]]`	false	The test value is a JSON array.
`[[isTypeNumber(WholeJSON.data.sales[0])]]`	true	The test value is a number.
`[[isTypeNumber(WholeJSON.data.manager)]]`	false	The test value is a JSON object.
`[[isTypeNumber(WholeJSON.data.manager.age)]]`	true	The test value is a number.
`[[isTypeNumber(WholeJSON.data.manager.married)]]`	false	The test value is a Boolean.

Using isTypeNumber in a conditional statement

Assume a "Describe a JSON Object" project with this data:

{
    "data": [
        {"branch": "Austin", "sales": 1345929.12, "target": 1250000},
        {"branch": "Boston", "sales": 1838534.77, "target": 1750000},
        {"branch": "Dallas", "sales": "no value", "target": 2000000},
        {"branch": "Denver", "sales": "no value", "target": 1750000}
    ]
}

The "data" array contains four JSON objects, each containing three key–value pairs.

Suppose you want the average sales value for this dataset. The standard approach is to map the array to a list of sales values, then calculate the average by using mean. For example:

[[

allSalesValues = map(WholeJSON.data, object -> object.sales)

mean(allSalesValues)]]

]]

This produces an error because the sales values for the third and fourth objects are non-numeric strings, which the mean function cannot handle. The mean function can handle nulls (by default, it ignores them), so here you could test if each sales value is a number and convert the non-numeric values to nulls. For example:

[[

allSalesValues = map(WholeJSON.data, object -> object.sales)

convertedSalesList = map(allSalesValues, value -> isTypeNumber(value) ? value : null)

avgSalesValue = mean(convertedSalesList)

"The average sales value is [[abbreviateNumber(currencyFormat(avgSalesValue))]]."

]]

The map function converts the list to:

(1345929.12, 1838534.77, null, null)

Now each value in the list is numeric or null, so you can calculate the average value.

The output text is:

The average sales value is $1.6M.

isTypeNumber

Parameters

Examples

Using isTypeNumber in a conditional statement

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