pyspark.sql.functions.contains(left, right)[source]# Returns a boolean. The value is True if right is found inside left. Returns NULL if either input expression is NULL. Otherwise, returns False. Both left or right must be of STRING or BINARY type. New in version 3.5.0.

>>> df = spark.createDataFrame( ... [(2, "Alice"), (5, "Bob")], ["age", "name"]) >>> df.filter(df.name.contains('o')).collect() [Row(age=5, name='Bob')]

Contains the other element. Returns a boolean Column based on a string match · string in line. A value as a literal or a Column

May 6, 2026 - PySpark SQL contains() function is used to match a column value contains in a literal string (matches on part of the string), this is mostly used to

Example 1: Basic usage of array_contains function. >>> from pyspark.sql import functions as sf >>> df = spark.createDataFrame([(["a", "b", "c"],), ([],)], ['data']) >>> df.select(sf.array_contains(df.data, "a")).show() +-----------------------+ |array_contains(data, a)| +-----------------------+ | true| | false| +-----------------------+ Example 2: Usage of array_contains function with a column.

June 4, 2026 - contains function in PySpark: Returns a boolean. The value is True if right is found inside left. Returns NULL if either input expression is NULL. Otherwise, returns False.

A Series of boolean values indicating whether the given pattern is contained within the string of each element of the Series.

June 4, 2026 - contains function in PySpark: Returns a boolean. The value is True if right is found inside left. Returns NULL if either input expression is NULL. Otherwise, returns False.

October 12, 2023 - #filter DataFrame where team column contains 'avs' df.filter(df.team.contains('avs')).show() The following example shows how to use this syntax in practice. Suppose we have the following PySpark DataFrame that contains information about points scored by various basketball players:

February 10, 2026 - In this code snippet, df.team references a specific column within the DataFrame named df. The contains(‘avs’) method is then invoked on that column, which generates a Boolean column expression.

October 12, 2023 - By default, the contains function in PySpark is case-sensitive.

June 4, 2026 - Column.contains method in PySpark: Check if a string column contains a substring.

PySpark Column's contains(~) method returns a Column object of booleans where True corresponds to column values that contain the specified substring.

>>> df.filter(df.name.contains('o')).collect() [Row(age=5, name='Bob')] pyspark.sql.Column.cast pyspark.sql.Column.desc

April 17, 2026 - Column.contains method in PySpark: Check if a string column contains a substring.

October 16, 2025 - The contains() method from pyspark.sql.functions provides exactly this capability.

May 6, 2026 - In Spark & PySpark, contains() function is used to match a column value contains in a literal string (matches on part of the string), this is mostly

November 17, 2025 - The PySpark framework uses the `filter()` method to select rows based on a conditional expression applied across one or more columns. When employing string matching, the condition is created by selecting the target column, applying the `contains` ...