R Programming in Data Science: High Variety Data.
(Online Course)

Book Cover
Average Rating
Published
Carpenteria, CA linkedin.com, 2018.
Format
Online Course
Status

Description

Loading Description...

Also in this Series

Checking series information...

More Like This

Loading more titles like this title...

More Details

Language
English

Notes

General Note
12/04/201812:00:00AM
Participants/Performers
Presenter: Mark Niemann-Ross
Description
High-variety data can cause a slew of problems for data scientists. In this course, learn what these problems are and how to use the unique capabilities of R to solve them.
Description
In a perfect world, every dataset would be stored as XML text with context for every piece of information. Numbers would never be stored as strings. Decimal values would never be stored as scientific notation. Strings would never be longer than 500 characters. But obviously, we don't live in a perfect world of data. And big data only makes this issue, well, bigger. This is the problem of variety; data arriving in multiple formats. Data scientists spend an inordinate amount of time with this problem, using brain power that would be better spent on valuable analysis tasks. In this course, Mark Niemann-Ross introduces the problem of data variety and demonstrates how to use the unique capabilities of R to solve them. Learn how to import a wide variety of data, from Excel to ODS files.
System Details
Latest version of the following browsers: Chrome, Safari, Firefox, or Internet Explorer. Adobe Flash Player Plugin. JavaScript and cookies must be enabled. A broadband Internet connection.

Citations

APA Citation, 7th Edition (style guide)

Niemann-Ross, M. (2018). R Programming in Data Science: High Variety Data . linkedin.com.

Chicago / Turabian - Author Date Citation, 17th Edition (style guide)

Niemann-Ross, Mark. 2018. R Programming in Data Science: High Variety Data. linkedin.com.

Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)

Niemann-Ross, Mark. R Programming in Data Science: High Variety Data linkedin.com, 2018.

MLA Citation, 9th Edition (style guide)

Niemann-Ross, Mark. R Programming in Data Science: High Variety Data linkedin.com, 2018.

Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.