pyspark.sql.functions.regexp_count#

pyspark.sql.functions.regexp_count(str, regexp)[source]#

Returns a count of the number of times that the Java regex pattern regexp is matched in the string str.

Added in version 3.5.0.

Parameters:

strColumn or column name: target column to work on. A column that evaluates to a string.
regexpColumn or column name: regex pattern to apply. A column that evaluates to a string.

Returns:

Column: the number of times that a Java regex pattern is matched in the string. Returns a column that evaluates to an integer.

Examples

>>> from pyspark.sql import functions as sf
>>> df = spark.createDataFrame([("1a 2b 14m", r"\d+")], ["str", "regexp"])
>>> df.select('*', sf.regexp_count('str', sf.lit(r'\d+'))).show()
+---------+------+----------------------+
|      str|regexp|regexp_count(str, \d+)|
+---------+------+----------------------+
|1a 2b 14m|   \d+|                     3|
+---------+------+----------------------+

>>> df.select('*', sf.regexp_count('str', sf.lit(r'mmm'))).show()
+---------+------+----------------------+
|      str|regexp|regexp_count(str, mmm)|
+---------+------+----------------------+
|1a 2b 14m|   \d+|                     0|
+---------+------+----------------------+

>>> df.select('*', sf.regexp_count("str", sf.col("regexp"))).show()
+---------+------+-------------------------+
|      str|regexp|regexp_count(str, regexp)|
+---------+------+-------------------------+
|1a 2b 14m|   \d+|                        3|
+---------+------+-------------------------+

>>> df.select('*', sf.regexp_count(sf.col('str'), "regexp")).show()
+---------+------+-------------------------+
|      str|regexp|regexp_count(str, regexp)|
+---------+------+-------------------------+
|1a 2b 14m|   \d+|                        3|
+---------+------+-------------------------+