How to Find Day of the Week in PySpark

You can use the following methods to find the day of the week for dates in a PySpark DataFrame:

Method 1: Get Day of Week as Number (Sunday =1)

import pyspark.sql.functions as F

df_new = df.withColumn('day_of_week', F.dayofweek('date'))

Method 2: Get Day of Week as Number (Monday=1)

import pyspark.sql.functions as F

df_new = df.withColumn('day_of_week', ((F.dayofweek('date')+5)%7)+1)

Method 3: Get Day of Week as Abbreviated Name (e.g. Mon)

import pyspark.sql.functions as F

df_new = df.withColumn('day_of_week', F.date_format('date', 'E'))

Method 4: Get Day of Week as Abbreviated Name (e.g. Monday)

import pyspark.sql.functions as F

df_new = df.withColumn('day_of_week', F.date_format('date', 'EEEE'))

The following examples show how to use each method in practice with the following PySpark DataFrame:

from pyspark.sql import SparkSession
spark = SparkSession.builder.getOrCreate()

#define data
data = [['2023-04-11', 22],
        ['2023-04-15', 14],
        ['2023-04-17', 12],
        ['2023-05-21', 15],
        ['2023-05-23', 30],
        ['2023-10-26', 45],
        ['2023-10-28', 32],
        ['2023-10-29', 47]]
  
#define column names
columns = ['date', 'sales']
  
#create dataframe using data and column names
df = spark.createDataFrame(data, columns) 
  
#view dataframe
df.show()

+----------+-----+
|      date|sales|
+----------+-----+
|2023-04-11|   22|
|2023-04-15|   14|
|2023-04-17|   12|
|2023-05-21|   15|
|2023-05-23|   30|
|2023-10-26|   45|
|2023-10-28|   32|
|2023-10-29|   47|
+----------+-----+

Example 1: Get Day of Week as Number (Sunday =1)

We can use the following syntax to get the day of the week as a number between 1 and 7, assuming Sunday is the start of the week:

import pyspark.sql.functions as F

#add new column that displays day of week as number
df_new = df.withColumn('day_of_week', F.dayofweek('date'))

#view new DataFrame
df_new.show()

+----------+-----+-----------+
|      date|sales|day_of_week|
+----------+-----+-----------+
|2023-04-11|   22|          3|
|2023-04-15|   14|          7|
|2023-04-17|   12|          2|
|2023-05-21|   15|          1|
|2023-05-23|   30|          3|
|2023-10-26|   45|          5|
|2023-10-28|   32|          7|
|2023-10-29|   47|          1|
+----------+-----+-----------+

Example 2: Get Day of Week as Number (Monday=1)

We can use the following syntax to get the day of the week as a number between 1 and 7, assuming Monday is the start of the week:

import pyspark.sql.functions as F

#add new column that displays day of week as number
df_new = df.withColumn('day_of_week', ((F.dayofweek('date')+5)%7)+1)

#view new DataFrame
df_new.show()

+----------+-----+-----------+
|      date|sales|day_of_week|
+----------+-----+-----------+
|2023-04-11|   22|          2|
|2023-04-15|   14|          6|
|2023-04-17|   12|          1|
|2023-05-21|   15|          7|
|2023-05-23|   30|          2|
|2023-10-26|   45|          4|
|2023-10-28|   32|          6|
|2023-10-29|   47|          7|
+----------+-----+-----------+

Example 3: Get Day of Week as Abbreviated Name

We can use the following syntax to get the day of the week as an abbreviated name:

import pyspark.sql.functions as F

#add new column that displays day of week as abbreviated name
df_new = df.withColumn('day_of_week', F.date_format('date', 'E'))

#view new DataFrame
df_new.show()

+----------+-----+-----------+
|      date|sales|day_of_week|
+----------+-----+-----------+
|2023-04-11|   22|        Tue|
|2023-04-15|   14|        Sat|
|2023-04-17|   12|        Mon|
|2023-05-21|   15|        Sun|
|2023-05-23|   30|        Tue|
|2023-10-26|   45|        Thu|
|2023-10-28|   32|        Sat|
|2023-10-29|   47|        Sun|
+----------+-----+-----------+

Example 4: Get Day of Week as Full Name

We can use the following syntax to get the day of the week as a full name:

import pyspark.sql.functions as F

#add new column that displays day of week as full name
df_new = df.withColumn('day_of_week', F.date_format('date', 'EEEE'))

#view new DataFrame
df_new.show()

+----------+-----+-----------+
|      date|sales|day_of_week|
+----------+-----+-----------+
|2023-04-11|   22|    Tuesday|
|2023-04-15|   14|   Saturday|
|2023-04-17|   12|     Monday|
|2023-05-21|   15|     Sunday|
|2023-05-23|   30|    Tuesday|
|2023-10-26|   45|   Thursday|
|2023-10-28|   32|   Saturday|
|2023-10-29|   47|     Sunday|
+----------+-----+-----------+