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Learner Reviews & Feedback for Handling Missing Values in R using tidyr by Coursera Project Network

About the Course

Missing data can be a “serious” headache for data analysts and scientists. This project-based course Handling Missing Values in R using tidyr is for people who are learning R and who seek useful ways for data cleaning and manipulation in R. In this project-based course, we will not only talk about missing values, but we will spend a great deal of our time here hands-on on how to handle missing value cases using the tidyr package. Be rest assured that you will learn a ton of good work here. By the end of this 2-hour-long project, you will calculate the proportion of missing values in the data and select columns that have missing values. Also, you will be able to use the drop_na(), replace_na(), and fill() function in the tidyr package to handle missing values. By extension, we will learn how to chain all the operations using the pipe function. This project-based course is an intermediate level course in R. Therefore, to complete this project, it is required that you have prior experience with using R. I recommend that you should complete the projects titled: “Getting Started with R” and “Data Manipulation with dplyr in R“ before you take this current project. These introductory projects in using R will provide every necessary foundation to complete this current project. However, if you are comfortable with using R, please join me on this wonderful ride! Let’s get our hands dirty!...
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1 - 1 of 1 Reviews for Handling Missing Values in R using tidyr

By Debalina M

Jun 20, 2023

The kind I was exactly looking for to sharpen my skills. Straightforward, goes directly to understanding the requirements and problem solving. A well guided brief project in R dealing with missing values.

Including the cases of missing values in categorical variables would have been more economical for this paid project.