pyspark.sql.functions.regexp_extract#

pyspark.sql.functions.regexp_extract(str, pattern, idx)[source]#

Extract a specific group matched by the Java regex regexp, from the specified string column. If the regex did not match, or the specified group did not match, an empty string is returned.

New in version 1.5.0.

Changed in version 3.4.0: Supports Spark Connect.

Parameters

strColumn or column name: target column to work on.
patternstr: regex pattern to apply.
idxint: matched group id.

Returns

Column: matched value specified by idx group id.

See also

pyspark.sql.functions.regexp_extract_all()

Examples

>>> from pyspark.sql import functions as sf
>>> df = spark.createDataFrame([('100-200',)], ['str'])
>>> df.select('*', sf.regexp_extract('str', r'(\d+)-(\d+)', 1)).show()
+-------+-----------------------------------+
|    str|regexp_extract(str, (\d+)-(\d+), 1)|
+-------+-----------------------------------+
|100-200|                                100|
+-------+-----------------------------------+

>>> df = spark.createDataFrame([('foo',)], ['str'])
>>> df.select('*', sf.regexp_extract('str', r'(\d+)', 1)).show()
+---+-----------------------------+
|str|regexp_extract(str, (\d+), 1)|
+---+-----------------------------+
|foo|                             |
+---+-----------------------------+

>>> df = spark.createDataFrame([('aaaac',)], ['str'])
>>> df.select('*', sf.regexp_extract(sf.col('str'), '(a+)(b)?(c)', 2)).show()
+-----+-----------------------------------+
|  str|regexp_extract(str, (a+)(b)?(c), 2)|
+-----+-----------------------------------+
|aaaac|                                   |
+-----+-----------------------------------+