diff --git a/docs/StardustDocs/topics/read.md b/docs/StardustDocs/topics/read.md
index e7bf2ef46a..e664f90587 100644
--- a/docs/StardustDocs/topics/read.md
+++ b/docs/StardustDocs/topics/read.md
@@ -170,6 +170,57 @@ val df = DataFrame.readCSV(
+### Work with specific date-time formats
+
+When parsing date or date-time columns, you might encounter formats different from the default `ISO_LOCAL_DATE_TIME`.
+Like:
+
+
+date |
+13/Jan/23 11:49 AM |
+14/Mar/23 5:35 PM |
+
+
+Because the format here `"dd/MMM/yy h:mm a"` differs from the default (`ISO_LOCAL_DATE_TIME`),
+columns like this may be recognized as simple `String` values rather than actual date-time columns.
+
+You can fix this whenever you [parse](parse.md) a string-based column (e.g., using [`DataFrame.readCSV()`](read.md#read-from-csv),
+[`DataFrame.readTSV()`](read.md#read-from-csv), or [`DataColumn.convertTo<>()`](convert.md)) by providing
+a custom date-time pattern. There are two ways to do this:
+
+1) By providing the date-time pattern as raw string to the `ParserOptions` argument:
+
+
+
+```kotlin
+val df = DataFrame.readCSV(
+ file,
+ parserOptions = ParserOptions(dateTimePattern = "dd/MMM/yy h:mm a")
+)
+```
+
+
+2) By providing a `DateTimeFormatter` to the `ParserOptions` argument:
+
+
+
+```kotlin
+val df = DataFrame.readCSV(
+ file,
+ parserOptions = ParserOptions(dateTimeFormatter = DateTimeFormatter.ofPattern("dd/MMM/yy h:mm a"))
+)
+```
+
+
+These two approaches are essentially the same, just specified in different ways.
+The result will be a dataframe with properly parsed `DateTime` columns.
+
+> Note: Although these examples focus on reading CSV files,
+> these `ParserOptions` can be supplied to any `String`-column-handling operation
+> (like, `readCsv`, `readTsv`, `stringCol.convertTo<>()`, etc.)
+> This allows you to configure the locale, null-strings, date-time patterns, and more.
+>
+> For more details on the parse operation, see the [`parse operation`](parse.md).
## Read from JSON