Data Wrangling in R
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Tidy data is a data format that provides a standardized way of organizing data values within a dataset. By leveraging tidy data principles, statisticians, analysts, and data scientists can spend less time cleaning data and more time tackling the more compelling aspects of data analysis. In this course, learn about the principles of tidy data, and discover how to create and manipulate data tibbles—transforming them from source data into tidy formats. Instructor Mike Chapple uses the R programming language and the tidyverse packages to teach the concept of data wrangling—the data cleaning and data transformation tasks that consume a substantial portion of analysts' time. He wraps up with three hands-on case studies that help to reinforce the data wrangling principles and tactics covered in this course.
Contents:
- Introduction
- 1. Tidy Data
- 2. Working with Tibbles
- 3. Importing Data into R
- 4. Data Transformation
- 5. Data Cleaning
- 6. Data Wrangling Case Study: Coal Consumption
- 7. Data Wrangling Case Study: Water Quality
- 8. Data Wrangling Case Study: Social Security Disability Claims
- Conclusion
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| Rating | Not enough ratings |
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| Length | 4h 12m |
| Starts | On Demand (Start anytime) |
| Cost | $29/month (Access to entire library- free trial available) |
| From | LinkedIn Learning |
| Instructor | Mike Chapple |
| Download Videos | Only via the LinkedIn Learning mobile app |
| Language | English |
| Subjects | IT & Networking Data Science Programming |
| Tags | IT Big Data R RStudio R (Programming Language) |
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| Rating | Not enough ratings |
|---|---|
| Length | 4h 12m |
| Starts | On Demand (Start anytime) |
| Cost | $29/month (Access to entire library- free trial available) |
| From | LinkedIn Learning |
| Instructor | Mike Chapple |
| Download Videos | Only via the LinkedIn Learning mobile app |
| Language | English |
| Subjects | IT & Networking Data Science Programming |
| Tags | IT Big Data R RStudio R (Programming Language) |
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