# Convert a timestamp column to a formatted string
<a name="transforms-format-timestamp"></a>

Format a timestamp column into a string based on a pattern. You can use *Format timestamp* to get date and time as a string with the desired format. You can define the format using [Spark date syntax](https://spark.apache.org/docs/latest/sql-ref-datetime-pattern.html) as well as most of the [Python date codes](https://docs.python.org/3/library/datetime.html#strftime-and-strptime-format-codes).

For example, if you want your date string to be formatted like “2023-01-01 00:00”, you can define such format using the Spark syntax as “yyyy-MM-dd HH:mm” or the equivalent Python date codes as “%Y-%m-%d %H:%M”

**To add a *Format timestamp* transform node in your job diagram**

1. Open the Resource panel and then choose **Format timestamp** to add a new transform to your job diagram. The node selected at the time of adding the node will be its parent.

1. (Optional) On the **Node properties** tab, you can enter a name for the node in the job diagram. If a node parent is not already selected, then choose a node from the **Node parents** list to use as the input source for the transform.

1. On the **Transform** tab, enter the name of the column to be converted.

1. On the **Transform** tab, enter the **Timestamp format** pattern to use, expressed using [Spark date syntax](https://spark.apache.org/docs/latest/sql-ref-datetime-pattern.html) or [Python date codes](https://docs.python.org/3/library/datetime.html#strftime-and-strptime-format-codes).

1. (Optional) On the **Transform** tab, instead of converting the selected column, you can create a new one and keep the original by entering a name for the new column.