R Programming: Advanced Analytics In R For Data Science Download
Take Your R & R Studio Skills To The Next Level. Data Analytics, Data Science, Statistical Analysis in Business, GGPlot2
What you’ll learn
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Perform Data Preparation in R
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Identify missing records in dataframes
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Locate missing data in your dataframes
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Apply the Median Imputation method to replace missing records
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Apply the Factual Analysis method to replace missing records
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Understand how to use the which() function
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Know how to reset the dataframe index
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Work with the gsub() and sub() functions for replacing strings
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Explain why NA is a third type of logical constant
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Deal with date-times in R
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Convert date-times into POSIXct time format
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Create, use, append, modify, rename, access, and subset Lists in R
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Understand when to use [] and when to use [[]] or the $ sign when working with Lists
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Create a timeseries plot in R
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Understand how the Apply family of functions works
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Recreate an apply statement with a for() loop
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Use apply() when working with matrices
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Use lapply() and sapply() when working with lists and vectors
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Add your own functions into apply statements
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Nest apply(), lapply() and sapply() functions within each other
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Use the which.max() and which.min() functions
Requirements
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Knowledge of the GGPlot2 package is recommended
- Basic knowledge of R
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Knowledge of dataframes
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Knowledge of vectors and vectorized operations
Description
Ready to take your R Programming skills to the next level?
Want to truly become proficient at Data Science and Analytics with R?
This course is for you!
Professional R Video training, unique datasets designed with years of industry experience in mind, engaging exercises that are both fun and also give you a taste for Analytics of the REAL WORLD.
In this course you will learn:
- How to prepare data for analysis in R
- How to perform the median imputation method in R
- What Lists are and how to use them
- How to use apply(), lapply() and sapply() instead of loops
- What the Apply family of functions is
- How to nest your own functions within apply-type functions
- How to nest apply(), lapply() and sapply() functions within each other
- And much, much more!
The more you learn the better you will get. After every module, you will already have a strong set of skills to take with you into your Data Science career.
Who this course is for:
- Anybody who has basic R knowledge and would like to take their skills to the next level
- Anybody who has already completed the R Programming A-Z course
- This course is NOT for complete beginners in R
R Programming: Advanced Analytics In R For Data Science Download
Source: https://www.udemy.com/course/r-analytics/
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