parse

Returns a DataFrame in which the given String columns are parsed into other types.

This is a special case of the convert operation.

df.parse()

To parse only particular columns use a column selector:

df.parse { age and weight }

parse tries to parse every String column into one of supported types in the following order:

• Int

• Long

• Instant (kotlinx.datetime and java.time)

• LocalDateTime (kotlinx.datetime and java.time)

• LocalDate (kotlinx.datetime and java.time)

• Duration (kotlin.time and java.time)

• LocalTime (java.time)

• URL (java.net)

• Double (with optional locale settings)

• Boolean

• BigDecimal

• JSON (arrays and objects)

Available parser options:

• locale: Locale is used to parse doubles

• dateTimePattern: String is used to parse date and time

• dateTimeFormatter: DateTimeFormatter is used to parse date and time

• nullStrings: List<String> is used to treat particular strings as null value. Default null strings are "null" and "NULL"

df.parse(options = ParserOptions(locale = Locale.CHINA, dateTimeFormatter = DateTimeFormatter.ISO_WEEK_DATE))

You can also set global parser options that will be used by default in read, convert, and parse operations:

DataFrame.parser.locale = Locale.FRANCE
DataFrame.parser.addDateTimePattern("dd.MM.uuuu HH:mm:ss")