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)
Argument | Required? | Data Type | Description |
---|---|---|---|
function_col_ref | Y | string | Name 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 Type | Example Value |
---|---|---|
Yes | Datetime (column reference) | datTransactions |
Tip: For additional examples, see Common Tasks.
Examples
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:
classId | Date1 | Date2 | Date3 |
---|---|---|---|
c001 | 2020-03-09 | 2020-03-13 | 2020-03-17 |
c002 | 2020-03-09 | 2020-03-06 | 2020-03-21 |
c003 | 2020-03-09 | 2020-03-16 | 2020-03-23 |
c004 | 2020-03-09 | 2020-03-23 | 2020-04-06 |
c005 | 2020-03-09 | 2020-04-09 | 2020-05-09 |
c006 | 2020-03-09 | 2020-08-09 | 2021-01-09 |
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:
classId | key | value |
---|---|---|
Same as previous. | DateX column identifier | Corresponding 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:
classId | key | eventDates | mostFrequentDate | latestDate | earliestDate |
---|---|---|---|---|---|
c001 | Date1 | 2020-03-09 | 2020-03-09 | 2021-01-09 | 2020-03-06 |
c001 | Date2 | 2020-03-13 | 2020-03-09 | 2021-01-09 | 2020-03-06 |
c001 | Date3 | 2020-03-17 | 2020-03-09 | 2021-01-09 | 2020-03-06 |
c002 | Date1 | 2020-03-09 | 2020-03-09 | 2021-01-09 | 2020-03-06 |
c002 | Date2 | 2020-03-06 | 2020-03-09 | 2021-01-09 | 2020-03-06 |
c002 | Date3 | 2020-03-21 | 2020-03-09 | 2021-01-09 | 2020-03-06 |
c003 | Date1 | 2020-03-09 | 2020-03-09 | 2021-01-09 | 2020-03-06 |
c003 | Date2 | 2020-03-16 | 2020-03-09 | 2021-01-09 | 2020-03-06 |
c003 | Date3 | 2020-03-23 | 2020-03-09 | 2021-01-09 | 2020-03-06 |
c004 | Date1 | 2020-03-09 | 2020-03-09 | 2021-01-09 | 2020-03-06 |
c004 | Date2 | 2020-03-23 | 2020-03-09 | 2021-01-09 | 2020-03-06 |
c004 | Date3 | 2020-04-06 | 2020-03-09 | 2021-01-09 | 2020-03-06 |
c005 | Date1 | 2020-03-09 | 2020-03-09 | 2021-01-09 | 2020-03-06 |
c005 | Date2 | 2020-04-09 | 2020-03-09 | 2021-01-09 | 2020-03-06 |
c005 | Date3 | 2020-05-09 | 2020-03-09 | 2021-01-09 | 2020-03-06 |
c006 | Date1 | 2020-03-09 | 2020-03-09 | 2021-01-09 | 2020-03-06 |
c006 | Date2 | 2020-08-09 | 2020-03-09 | 2021-01-09 | 2020-03-06 |
c006 | Date3 | 2021-01-09 | 2020-03-09 | 2021-01-09 | 2020-03-06 |
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