to_number

Convert string 'col' to a number based on the string format '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 string. If the 0/9 sequence starts with 0 and is before the decimal point, it can only match a digit sequence of the same size. Otherwise, if the sequence starts with 9 or is after the decimal point, it can match a digit sequence that has the same or smaller size.
'.' 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. 'col' must match the grouping separator relevant for the size of the number.
'$': Specifies the location of the $ 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' allows '-' but 'MI' does not.
'PR': Only allowed at the end of the format string; specifies that 'col' indicates a negative number with wrapping angled brackets.

For the corresponding Databricks SQL function, see to_number function.

Syntax

Python
from pyspark.sql import functions as dbf

dbf.to_number(col=<col>, format=<format>)

Parameter	Type	Description
`col`	`pyspark.sql.Column` or `str`	Input column or strings.
`format`	`pyspark.sql.Column` or `str, optional`	format to use to convert number values.

Python
df = spark.createDataFrame([("$78.12",)], ["e"])
df.select(to_number(df.e, lit("$99.99")).alias('r')).collect()