R Programming: Advanced Analytics In R For Data Science Download
R Programming, Take the R & R Studio Skills To The Next Level. Data Analytics, Data Sciences, Business Statistical Analysis, ggplot2
What you will learn
- Preparation Perform Data in R
- Identify missing records in data frames
- Searching for the missing data in your data frames
- Applying the median imputation method to replace the missing records
- Applying the Factual Analysis method to replace the missing records
- Understanding how to use the () function
- Know how to reset the index data frame
- Working with sub () and sub () function to replace string
- Explain why NA is the third type of logical constant
- Dealing with dates and times in R
- Convert date-time format time to POSIXct
- Make, use, append, modify, rename, and Access Lists section in the R
- basic knowledge of R
- Knowledge of ggplot2 package recommended
- Knowledge of data frames
- Knowledge of vector and vectorized operations
Ready to take your R Programming skills to the next level?
Want to really become proficient at Data Science and Analytics with R?
This course is for you!
professional training R Video, a unique dataset that is designed with many years of industry experience in mind, interesting exercises that are both fun and also provide a sense of REAL WORLD Analytics.
In this course you will learn:
- How to prepare data for analysis in R
- How to perform a median imputation method in R
- How to work with dates and times in R
- List of What and how to use it
- What is the function of the family Apply
- How to use apply (), apply () and apply () instead of loops
- How to nest your own functions in implementing the type of function
- How to apply nest (), apply () and apply () function in each other
- And many more!
The more you learn the better you will get. After each module, you will already have a strong set of skills to take with you to your data science careers.
Who this course is for:
- Anyone who has knowledge of the basic R and want to take their skills to the next level
- Anyone who has completed the R Programming A-Z of course
- Of course, this is not for complete beginners in R
Created by Kirill Eremenko, SuperDataScience Team
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