Lab
A Cloud Guru

Cleanse Outlying Data Using the pandas Python Package

In this lab, we will load a CSV file into a pandas DataFrame. Once loaded, we will remove rows with an `age` more than 3 standard deviations from the mean and rows with `hours-per-week` below the 10% and above the 90% quantiles. We will then write the cleansed data to a file. Basic Python programming skills will be required for this lab. If you need a refresher, check out the following course: - [Certified Associate in Python Programming Certification](https://acloud.guru/overview/8169e8e7-91a7-4d92-b278-4dd08c787dc6)

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Path Info

Level

Intermediate

Duration

30m

Published

Jun 04, 2021

Challenge

Load the Data File

Load the data.csv file into a pandas DataFrame.
Challenge

Resolve Outlying age Values

Remove rows with an age more than 3 standard deviations from the mean.
Challenge

Resolve Outlying hours-per-week Values

Remove rows with hours-per-week below the 10% and above the 90% quantiles.
Challenge

Write the Data to a New File

Write the data to a new file named cleaned_data.csv.

Author

A Cloud Guru

The Cloud Content team comprises subject matter experts hyper focused on services offered by the leading cloud vendors (AWS, GCP, and Azure), as well as cloud-related technologies such as Linux and DevOps. The team is thrilled to share their knowledge to help you build modern tech solutions from the ground up, secure and optimize your environments, and so much more!

What's a lab?

Hands-on Labs are real environments created by industry experts to help you learn. These environments help you gain knowledge and experience, practice without compromising your system, test without risk, destroy without fear, and let you learn from your mistakes. Hands-on Labs: practice your skills before delivering in the real world.