How to validate the date format of a column in Pyspark?

Question

I am really new to Pyspark, I want to check if the column has the correct date format or not? How do I do it? I have tried though I am getting an error. Can anyone help me with this?

My code:

df = 
   Date        name
0  12/12/2020   a
1  24/01/2019   b
2  08/09/2018   c
3  12/24/2020   d
4  Nan          e
df_out= df.withColumn('output', F.when(F.to_date("Date","dd/mm/yyyy").isNotNull, Y).otherwise(No))
df_out.show()

gives me:

TypeError: condition should be a Column

Answer 1

You can filter out the rows after converting to date type.

Example:

df.show()
#+----------+----+
#|      Date|name|
#+----------+----+
#|12/12/2020|   a|
#|24/01/2019|   b|
#|12/24/2020|   d|
#|       nan|   e|
#+----------+----+

from pyspark.sql.functions import *

df.withColumn("output",to_date(col('Date'),'dd/MM/yyyy')).\
filter(col("output").isNotNull()).\
show()
#+----------+----+----------+
#|      Date|name|    output|
#+----------+----+----------+
#|12/12/2020|   a|2020-12-12|
#|24/01/2019|   b|2019-01-24|
#+----------+----+----------+

#without adding new column
df.filter(to_date(col('Date'),'dd/MM/yyyy').isNotNull()).show()
#+----------+----+
#|      Date|name|
#+----------+----+
#|12/12/2020|   a|
#|24/01/2019|   b|
#+----------+----+