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Instructor: Dr. Nikunj Maheshwari
3,842 already enrolled
Included with
(91 reviews)
Recommended experience
Beginner level
The learner should know how information is stored in rows and columns in a table.
(91 reviews)
Recommended experience
Beginner level
The learner should know how information is stored in rows and columns in a table.
Learn how to calculate descriptive statistical metrics in order to describe a dataset in basic R
Create a data quality report file (exported to Excel in CSV format) from a dataset loaded in R
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Only available on desktop
By the end of this project, you will create a data quality report file (exported to Excel in CSV format) from a dataset loaded in R, a free, open-source program that you can download. You will learn how to use the following descriptive statistical metrics in order to describe a dataset and how to calculate them in basic R with no additional libraries.
- minimum value - maximum value - average value - standard deviation - total number of values - missing values - unique values - data types You will then learn how to record the statistical metrics for each column of a dataset using a custom function created by you in R. The output of the function will be a ready-to-use data quality report. Finally, you will learn how to export this report to an external file. A data quality report can be used to identify outliers, missing values, data types, anomalies, etc. that are present in your dataset. This is the first step to understand your dataset and let you plan what pre-processing steps are required to make your dataset ready for analysis. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Load and view a real-world dataset in RStudio (5 min)
Calculate Measure of Frequency metrics (5 min)
Calculate Measure of Central Tendency metrics (6 min)
Calculate Measure of Dispersion metrics (4 min)
Calculate additional data quality metrics (6 min)
Calculate descriptive statistics on all columns (10 min)
Generate a data quality report file (8 min)
The learner should know how information is stored in rows and columns in a table.
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Skill-based, hands-on learning
Practice new skills by completing job-related tasks.
Expert guidance
Follow along with pre-recorded videos from experts using a unique side-by-side interface.
No downloads or installation required
Access the tools and resources you need in a pre-configured cloud workspace.
Available only on desktop
This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
91 reviews
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Reviewed on Jul 18, 2020
It was a bit challenging to follow towards the end, but overall it was a good project.
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Duke University
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Johns Hopkins University
Course
Johns Hopkins University
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By purchasing a Guided Project, you'll get everything you need to complete the Guided Project including access to a cloud desktop workspace through your web browser that contains the files and software you need to get started, plus step-by-step video instruction from a subject matter expert.
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At the top of the page, you can press on the experience level for this Guided Project to view any knowledge prerequisites. For every level of Guided Project, your instructor will walk you through step-by-step.
Yes, everything you need to complete your Guided Project will be available in a cloud desktop that is available in your browser.
You'll learn by doing through completing tasks in a split-screen environment directly in your browser. On the left side of the screen, you'll complete the task in your workspace. On the right side of the screen, you'll watch an instructor walk you through the project, step-by-step.