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Computes the maximum value found in all row values in a Datetime column.

If a row contains a missing or null value, it is not factored into the calculation. If no Datetime values are found in the source column, the function returns a null value.

Wrangle vs. SQL: This function is part of Wrangle, a proprietary data transformation language. Wrangle is not SQL. For more information, see Wrangle Language.


Basic Usage

maxdate(myDates)

Output: Returns the maximum Datetime value from the myDates column.

Syntax and Arguments

maxdate(function_col_ref)


ArgumentRequired?Data TypeDescription
function_col_refYstringName of column to which to apply the function


For more information on syntax standards, see Language Documentation Syntax Notes.

function_col_ref

Name of the column the Datetime values of which you want to calculate the maximum date.

  • Column must contain Datetime values.
  • Literal values are not supported as inputs.
  • Multiple columns and wildcards are not supported.

Usage Notes:

Required?Data TypeExample Value
YesDatetime (column reference)datTransactions


Examples

Tip: For additional examples, see Common Tasks.

This example shows how you can use the following functions to perform some analysis on Datetime columns.
  • MINDATE - Calculates the earliest (minimum) date from a column of Datetime column values. See MINDATE Function.
  • MAXDATE - Calculates the latest (maximum) date from a column of Datetime column values. See MAXDATE Function.
  • MODEDATE - Calculates the most frequent (mode) date from a column of Datetime column values. See MODEDATE Function.

Source:

The following dataset contains a set of three available dates for a set of classes:

classIdDate1Date2Date3
c0012020-03-092020-03-132020-03-17
c0022020-03-092020-03-062020-03-21
c0032020-03-092020-03-162020-03-23
c0042020-03-092020-03-232020-04-06
c0052020-03-092020-04-092020-05-09
c0062020-03-092020-08-092021-01-09

Transformation: 

To compare dates across multiple columns, you must consolidate the values into a single column. You can use the following transformation to do so:

Transformation Name Unpivot columns
Parameter: Columns Date1,Date2,Date3
Parameter: Group size 1

The dataset is now contained in three columns, with descriptions listed below:

classIdkeyvalue
Same as previous.DateX column identifierCorresponding value from the DateX column.

You can use the following to rename the value column to eventDates:

Transformation Name Rename columns
Parameter: Option Manual rename
Parameter: Column value
Parameter: New column name eventDates

Using the following transformations, you can create new columns containing the min, max, and mode values for the Datetime values in eventDates:

Transformation Name New formula
Parameter: Formula type Single row formula
Parameter: Formula MINDATE(eventDates)
Parameter: New column name earliestDate

Transformation Name New formula
Parameter: Formula type Single row formula
Parameter: Formula MAXDATE(eventDates)
Parameter: New column name latestDate

Transformation Name New formula
Parameter: Formula type Single row formula
Parameter: Formula MODEDATE(eventDates)
Parameter: New column name mostFrequentDate

Results:

classIdkeyeventDatesmostFrequentDatelatestDateearliestDate
c001Date12020-03-092020-03-092021-01-092020-03-06
c001Date22020-03-132020-03-092021-01-092020-03-06
c001Date32020-03-172020-03-092021-01-092020-03-06
c002Date12020-03-092020-03-092021-01-092020-03-06
c002Date22020-03-062020-03-092021-01-092020-03-06
c002Date32020-03-212020-03-092021-01-092020-03-06
c003Date12020-03-092020-03-092021-01-092020-03-06
c003Date22020-03-162020-03-092021-01-092020-03-06
c003Date32020-03-232020-03-092021-01-092020-03-06
c004Date12020-03-092020-03-092021-01-092020-03-06
c004Date22020-03-232020-03-092021-01-092020-03-06
c004Date32020-04-062020-03-092021-01-092020-03-06
c005Date12020-03-092020-03-092021-01-092020-03-06
c005Date22020-04-092020-03-092021-01-092020-03-06
c005Date32020-05-092020-03-092021-01-092020-03-06
c006Date12020-03-092020-03-092021-01-092020-03-06
c006Date22020-08-092020-03-092021-01-092020-03-06
c006Date32021-01-092020-03-092021-01-092020-03-06

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