pyspark.sql.functions.to_varchar��
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pyspark.sql.functions.
to_varchar
(col: ColumnOrName, format: ColumnOrName) → pyspark.sql.column.Column[source]�� Convert col to a string based on the format. Throws an exception if the conversion fails. The format can consist of the following characters, case insensitive: ���0��� or ���9���: Specifies an expected digit between 0 and 9. A sequence of 0 or 9 in the format string matches a sequence of digits in the input value, generating a result string of the same length as the corresponding sequence in the format string. The result string is left-padded with zeros if the 0/9 sequence comprises more digits than the matching part of the decimal value, starts with 0, and is before the decimal point. Otherwise, it is padded with spaces. ���.��� or ���D���: Specifies the position of the decimal point (optional, only allowed once). ���,��� or ���G���: Specifies the position of the grouping (thousands) separator (,). There must be a 0 or 9 to the left and right of each grouping separator. ������:Specifiesthelocationofthe currency sign. This character may only be specified once. ���S��� or ���MI���: Specifies the position of a ���-��� or ���+��� sign (optional, only allowed once at the beginning or end of the format string). Note that ���S��� prints ���+��� for positive values but ���MI��� prints a space. ���PR���: Only allowed at the end of the format string; specifies that the result string will be wrapped by angle brackets if the input value is negative.
New in version 3.5.0.
- Parameters
Examples
>>> df = spark.createDataFrame([(78.12,)], ["e"]) >>> df.select(to_varchar(df.e, lit("$99.99")).alias('r')).collect() [Row(r='$78.12')]