Data Science with R Programming training course has been designed to prepare you for a great opportunity in the analytics space. R Programming is the most used programming language, today in the data science and analytics field. Since it's an open source in nature and very powerful, R is becoming the language of choice of data scientists around the world. R is first step in the field of data science and a must-have for every data scientist.
INTRODUCTION TO R
- What is R
- Features of R
- SAS versus R
- Obtaining and managing R
- Installing R
- Packages
- R interfaces
- R Library
Data Structure
- Vector – Numeric and character
- Factor
- Matrix
- Data Frame
- List
Basic of R
- NA
- Missing
- Multiplication
- Missing value
- Convert numeric variable to character
- Convert numeric variable to numeric
- Mode
- Class
Inbuilt Functions of R
- Environment functions
- Statistical Functions
- Text Functions
- Mathematical Functions
- Create data in r
- Reading data in R from various sources
- Writing data (export data) from R
Control Structure of R
- If and else
- For
- Repeat
- While
Loop Function of R
- Apply
- Sapply
- Lapply
- Split
Transpose
- Wide structure to long
- Long structure to wide
Merging
- Inner
- Left
- Right
- Full
- Cross
Data manipulation
- Sampling
- Filter
- Grouping
- Summarization
- Distinct
- Select
- Arrange
- Mutate
- Rank
Date and time in R
- Dates in R
- Time in R
- Operation on Dates and Time on R
Graphs in R
- Creating a graph
- Density Plot
- Dot Plot
- Bar Plot
- Line Charts
- Pie Charts
- Box Plot
- Scatter Plot
- Histogram
Character Function
- Is Character
- Paste
- Sprint
- Substr
- Nchar
- Sub
- Word
- To-lower
- To-upper
- Trimws
- Clean
