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get year information from a timestamp data frame
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get year information from a timestamp data frame
Hi all,
I am new to python.
I am reading a datafile where there is timestamp values as string.
I want to ger distinct years from this dataframe and keep them in an array.
I have some trial below that don't work.
Could you give a help about how to do it

import pyspark
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName('pyspark-by-examples').getOrCreate()
from pyspark.sql.types import StructType,StructField, StringType, IntegerType,ArrayType
from pyspark.sql.functions import split, explode
import pyspark.sql.types 

import calendar
import datetime
import pandas as pd
from pyspark.sql import functions as F
from pyspark.sql import types as T
import datetime as dt 

arrayData ="delta").load("/mnt/datalake/....something")
#arraySchema = StructType([ \
   # StructField("repair_year",StringType(),True), \

arrayData['repair_year']='repair_date').withColumn("repair_date", F.col("repair_date").cast(T.TimestampType()))

#df = arraySchema
buran write Jan-08-2021, 04:52 PM:
Please, use proper tags when post code, traceback, output, etc. This time I have added tags for you.
See BBcode help for more info.
import datetime
import time

# create a timestamp -- you won't have to do this as you already have timestamp
timestamp = time.time()
print(f"\n\ntimestamp: {timestamp}")

year =
print(f"Year: {year}")
timestamp: 1610140280.269422 Year: 2021

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