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Convert string 'col' to a number based on the string format format. Returns NULL if the string 'col' does not match the expected format. The format follows the same semantics as the to_number function.
For the corresponding Databricks SQL function, see try_to_number function.
Syntax
from pyspark.databricks.sql import functions as dbf
dbf.try_to_number(col=<col>, format=<format>)
Parameters
| 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. |
Examples
from pyspark.databricks.sql import functions as dbf
df = spark.createDataFrame([("$78.12",)], ["e"])
df.select(dbf.try_to_number(df.e, dbf.lit("$99.99")).alias('r')).show()
origin = spark.conf.get("spark.sql.ansi.enabled")
spark.conf.set("spark.sql.ansi.enabled", "true")
try:
df = spark.range(1)
df.select(dbf.try_to_number(dbf.lit("77"), dbf.lit("$99.99")).alias('r')).show()
finally:
spark.conf.set("spark.sql.ansi.enabled", origin)