Skip to main content
HomeSpark

Project

Cleaning an Orders Dataset with PySpark

AdvancedSkill Level
4.8+
200 reviews
Updated 07/2024
Step into a data engineer's shoes and master data cleaning with PySpark on an e-commerce orders dataset!
Start Project

Included withPremium or Teams

SparkData EngineeringData Preparation1 hr1 Task1,500 XP2,814

Create Your Free Account

or

By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.
Group

Training 2 or more people?

Try DataCamp for Business

Loved by learners at thousands of companies

Project Description

Cleaning an Orders Dataset with PySpark

Data cleaning is an essential skill for any data professional.In this project, you will step into a role of a data engineer at an e-commerce company and use PySpark, a powerful tool for data processing, to clean an orders dataset.This hands-on experience will sharpen your ability to format, extract and amend data for further analysis.

Cleaning an Orders Dataset with PySpark

Step into a data engineer's shoes and master data cleaning with PySpark on an e-commerce orders dataset!
Start Project
  • 1

    Task 1

Don’t just take our word for it

*4.8
from 200 reviews
84%
16%
0%
0%
0%
  • Mohammed
    19 hours ago

  • László
    4 days ago

    It was really interesting and a good exercise in general. I just don't understand why it didn't accept my filtering solution for "tv", which was identical to the one within the official solution

  • Eduardo
    5 days ago

  • Vijaya
    6 days ago

  • wittawat
    2 weeks ago

  • wittawat
    2 weeks ago

Mohammed

"It was really interesting and a good exercise in general. I just don't understand why it didn't accept my filtering solution for "tv", which was identical to the one within the official solution"

László

Eduardo

    Join over 18 million learners and start Cleaning an Orders Dataset with PySpark today!

    Create Your Free Account

    or

    By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.