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Cleaning Data with R

Cleaning data accounts for 70-80% of an analyst’s time. This skill teaches you how to understand the nature of your data, identify problem areas, and then clean the data set to enable your analysis using R.

What You'll Learn

This skill conveys R-based solutions for the most common data cleaning operations encountered in the analytics workflow. The skill and courses should be structured around data-centric topics, rather than language or package features.

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What's inside

Three courses

Querying and Converting Data Types in R

(2 hours)

Get started with R and learn how to work with different data types. Understand the most powerful data format, the Data Frame, and learn how to query this format.

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Manipulating Dataframes in R

(1 hours)

People coming from spreadsheets are blown away with how easy and powerful it is to manipulate tabular data with R. In this course, you will learn the fundamental building blocks of working with the R data frame.

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Coping with Missing, Invalid, and Duplicate Data in R

(2 hours)

Learn the essential steps of data preparation: Missing value imputation, outlier detection, and duplicate removal. Data preparation is part of nearly any data analytics project, therefore the skills are highly valuable.

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Time

333 hours

Via

Pluralsight

Institution

Instructors

Martin Burger

Chase DeHan

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