• Inputs can be of any type. 
  • If the input is not a Datetime value and does match one of the specified formats, the output is in the following format: yyyy-MM-dd HH:mm:ss.
  • If the input is a Datetime value and does match, the output is in the input's Datetime format.

After you have converted your strings values to dates, if a sufficient percentage of input strings from a column are successfully converted to one of the matching formats, the column may be retyped as Datetime.

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  supports a wide variety of formats for Datetime fields. For more information on supported date formats, see Datetime Data Type.
• You can explore the available Datetime formats through the Transformer page. From a column's type drop-down, select Date/Time . Then, select the formatting category. From the displayed drop-down, you can select a specific format. When this transform step is added to your recipe, you can edit it to see how the format is specified in

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• You can then use the DATEFORMAT function to convert the output values to your preferred Datetime format. See DATEFORMAT Function.

Output: Returns a value structured in  yyyy-MM-dd HH:mm:ss  format if the input value in strDate matches any of default formats, which are the following:

'yyyy-MM-dd HH:mm:ss' 
'yyyy/MM/dd HH:mm:ss' 
'yyyy-MM-dd' 
'yyyy/MM/dd'

Output: Returns a value structured in  yyyy-MM-dd HH:mm:ss  format if the input value in strDate matches any of the listed formats for dates.

date_col

Literal, column name, or function returning values that are to be evaluated for conversion to Datetime values.

• Inputs values can be of any type. 
• Missing values for this function in the source data result in null values in the output.
• Multiple columns and wildcards are not supported.

date_formats_array

Array of String values of the date formats to evaluate the inputs.

• When a non-Datetime input value matches one of the date formats in the array, the output is the input value converted to the following format:

yyyy-MM-dd HH:mm:ss

• Datetime inputs are outputted in their source format.

For more information on supported date formats, see Datetime Data Type.

Example - formatting date values

This example illustrates several ways of wrangling heterogeneous date values, including the use of the DATEFORMAT function.

Source:

Your dataset includes the following messy date values:

Transformation:

To enable easier comparison in the data grid, you choose to create a new column with the parsed values. From the above, you identify two date formats:

'MM/dd/yy hh:mm'
'MM/dd/YYYY hh:mm:ss'

You create the following transformation to parse them:

When the above step is added to the recipe, the output is as follows:

The output myParsedDates column is retyped as a Datetime column with one mismatched value: 3/7/1999 22:00.

This value does not match any of our date formats specified in the array. The solution is to modify the recipe step to include the appropriate format as part of the array:

Results:

For more information on supported date formats, see Datetime Data Type.

Example - type parsing functions