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You can use the following methods to extract the minutes from a timestamp in PySpark:

Method 1: Extract Minutes from Timestamp

from pyspark.sql import functions as F

df_new = df.withColumn('minutes', F.minute(df['ts']))

If the timestamp is 2023-01-15 04:14:22 then this syntax would return 14.

Method 2: Extract Timestamp Truncated to Minutes

from pyspark.sql import functions as F

df_new = df.withColumn('minutes', F.date_trunc('minute', df['ts']))

If the timestamp is 2023-01-15 04:14:22 then this syntax would return 2023-01-15 04:14:00.

The following example shows how to use each method in practice with the following PySpark DataFrame that contains information about sales made on various timestamps at some company:

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

from pyspark.sql import functions as F

#define data
data = [['2023-01-15 04:14:22', 225],
        ['2023-02-24 10:55:01', 260],
        ['2023-07-14 18:34:59', 413],
        ['2023-10-30 22:20:05', 368]] 
  
#define column names
columns = ['ts', 'sales'] 
  
#create dataframe using data and column names
df = spark.createDataFrame(data, columns)

#convert string column to timestamp
df = df.withColumn('ts', F.to_timestamp('ts', 'yyyy-MM-dd HH:mm:ss'))
  
#view dataframe
df.show()

+-------------------+-----+
|                 ts|sales|
+-------------------+-----+
|2023-01-15 04:14:22|  225|
|2023-02-24 10:55:01|  260|
|2023-07-14 18:34:59|  413|
|2023-10-30 22:20:05|  368|
+-------------------+-----+

Example 1: Extract Minutes from Timestamp

We can use the following syntax to extract only the minutes from each timestamp in the ts column of the DataFrame:

from pyspark.sql import functions as F

#extract minutes from each timestamp in 'ts' column
df_new = df.withColumn('minutes', F.minute(df['ts']))

#view new DataFrame
df_new.show()

+-------------------+-----+-------+
|                 ts|sales|minutes|
+-------------------+-----+-------+
|2023-01-15 04:14:22|  225|     14|
|2023-02-24 10:55:01|  260|     55|
|2023-07-14 18:34:59|  413|     34|
|2023-10-30 22:20:05|  368|     20|
+-------------------+-----+-------+

The new minutes column shows only the minutes from each timestamp in the ts column.

Example 2: Extract Timestamp Truncated to Minutes

We can use the following syntax to return each timestamp from the ts column truncated to the minutes:

from pyspark.sql import functions as F

#create new column that contains timestamp truncated to the minutes
df_new = df.withColumn('minutes', F.date_trunc('minute', df['ts']))

#view new DataFrame
df_new.show()

+-------------------+-----+-------------------+
|                 ts|sales|            minutes|
+-------------------+-----+-------------------+
|2023-01-15 04:14:22|  225|2023-01-15 04:14:00|
|2023-02-24 10:55:01|  260|2023-02-24 10:55:00|
|2023-07-14 18:34:59|  413|2023-07-14 18:34:00|
|2023-10-30 22:20:05|  368|2023-10-30 22:20:00|
+-------------------+-----+-------------------+

The new minutes column shows each timestamp from the ts column truncated to the minutes.

Additional Resources

The following tutorials explain how to perform other common tasks in PySpark: