JS Problems geeksforgeeks Exercises and Solutions for Beginners

How to Convert a DataFrame Column Type from String to Timestamp in PySpark [All Method]️

The step-by-step guide on this page will show you How to Convert a DataFrame Column Type from String to Timestamp in PySpark. By following this guide, you will be able to deal with these sorts of difficulties.
Question: What is the best way to approach this problem? Answer: Check out this blog code to learn how to fix errors How to Convert a DataFrame Column Type from String to Timestamp in PySpark. Question: What is causing this error and what can be done to fix it? Answer: Check out this blog for a solution to your problem.

How can we convert a column type from string to timestamp in a PySpark DataFrame?

Suppose we have a DataFrame df with column date of type string.

This column might have strings like this:

2022-01-04 10:41:05

Or maybe something funky like this:

2022_01_04 10_41_05

Let’s say we want to cast either of these columns into type timestamp.

Luckily, Column provides a cast() method to convert columns into a specified data type.

Cast standard timestamp formats

If our timestamp is standard (i.e. follows the yyyy-MM-dd HH:mm:ss.SSSS format), we can use either cast() or to_timestamp() to perform the cast.

Let’s say we wanted to cast the string 2022-01-04 10:41:05.

Cast using cast()

Here’s how we can cast using cast().

from pyspark.sql.types import TimestampType
df = df.withColumn("date", df["date"].cast(TimestampType()))

We can also use col() with simple strings.

from pyspark.sql.functions import col
df = df.withColumn("date", col("date").cast("timestamp"))

Cast using to_timestamp()

Here’s how we can cast using to_timestamp().

from pyspark.sql.functions import to_timestamp
from pyspark.sql.types import TimestampType
df = df.withColumn("date", to_timestamp("date", TimestampType())) 

Keep in mind that both of these methods require the timestamp to follow this yyyy-MM-dd HH:mm:ss.SSSS format.

Read more on to_timestamp() here.

Cast abnormal timestamp formats

If we want to cast an abnormally formatted string into a timestamp, we’ll have to specify the format in to_timestamp().

Let’s say we wanted to cast the string 2022_01_04 10_41_05.

Cast using to_timestamp()

If we’re running Spark 2.2 or higher, we can cast easily with to_timestamp().

from pyspark.sql.functions import to_timestamp
df = df.withColumn("date", to_timestamp("date", "yyyy_MM_dd HH_mm_ss"))

Cast using unix_timestamp()

If we’re running < Spark 2.2, we can cast easily with unix_timestamp().

from pyspark.sql.functions import unix_timestamp
df = df.withColumn("date", unix_timestamp("date", "yyyy_MM_dd HH_mm_ss"))

Quick caveat: unix_timestamp() only has second-precision, as opposed to millisecond-precision. If we’re working with a standard format, it’s desired to just use the cast() method above, which can handle milliseconds.


Now you learned, How you can use & How to Convert a DataFrame Column Type from String to Timestamp in PySpark.
Final Note: Try to Avoid this type of mistake(error) in future!

Related Articles

Leave a Reply

Your email address will not be published.

Back to top button