pyspark.sql.functions.quarter

pyspark.sql.functions.quarter(col)

Extract the quarter of a given date/timestamp as integer.

New in version 1.5.0.

Changed in version 3.4.0: Supports Spark Connect.

Parameters

colColumn or column name

target date/timestamp column to work on.

Returns

Column

quarter of the date/timestamp as integer.

See also

pyspark.sql.functions.year()

pyspark.sql.functions.month()

pyspark.sql.functions.day()

pyspark.sql.functions.hour()

pyspark.sql.functions.minute()

pyspark.sql.functions.second()

pyspark.sql.functions.extract()

pyspark.sql.functions.datepart()

pyspark.sql.functions.date_part()

Examples

Example 1: Extract the quarter from a string column representing dates

>>> from pyspark.sql import functions as sf
>>> df = spark.createDataFrame([('2015-04-08',), ('2024-10-31',)], ['dt'])
>>> df.select("*", sf.typeof('dt'), sf.quarter('dt')).show()
+----------+----------+-----------+
|        dt|typeof(dt)|quarter(dt)|
+----------+----------+-----------+
|2015-04-08|    string|          2|
|2024-10-31|    string|          4|
+----------+----------+-----------+

Example 2: Extract the quarter from a string column representing timestamp

>>> from pyspark.sql import functions as sf
>>> df = spark.createDataFrame([('2015-04-08 13:08:15',), ('2024-10-31 10:09:16',)], ['ts'])
>>> df.select("*", sf.typeof('ts'), sf.quarter('ts')).show()
+-------------------+----------+-----------+
|                 ts|typeof(ts)|quarter(ts)|
+-------------------+----------+-----------+
|2015-04-08 13:08:15|    string|          2|
|2024-10-31 10:09:16|    string|          4|
+-------------------+----------+-----------+

Example 3: Extract the quarter from a date column

>>> import datetime
>>> from pyspark.sql import functions as sf
>>> df = spark.createDataFrame([
...     (datetime.date(2015, 4, 8),),
...     (datetime.date(2024, 10, 31),)], ['dt'])
>>> df.select("*", sf.typeof('dt'), sf.quarter('dt')).show()
+----------+----------+-----------+
|        dt|typeof(dt)|quarter(dt)|
+----------+----------+-----------+
|2015-04-08|      date|          2|
|2024-10-31|      date|          4|
+----------+----------+-----------+

Example 4: Extract the quarter from a timestamp column

>>> import datetime
>>> from pyspark.sql import functions as sf
>>> df = spark.createDataFrame([
...     (datetime.datetime(2015, 4, 8, 13, 8, 15),),
...     (datetime.datetime(2024, 10, 31, 10, 9, 16),)], ['ts'])
>>> df.select("*", sf.typeof('ts'), sf.quarter('ts')).show()
+-------------------+----------+-----------+
|                 ts|typeof(ts)|quarter(ts)|
+-------------------+----------+-----------+
|2015-04-08 13:08:15| timestamp|          2|
|2024-10-31 10:09:16| timestamp|          4|
+-------------------+----------+-----------+