Data Science with R Programming Course Content
Essential to R programming
An Introduction to R
- History of R
- Introduction to R
- The R environment
- What is Statistical Programming?
- Why use a command line?
- Your first R session
Introduction to the R language
- Starting and quitting R
- Recording your work
Basic features of R
- Calculating with R
- Named storage
- Functions
- Exact or approximate?
- R is case-sensitive
- Listing the objects in the workspace
- Vectors
- Extracting elements from vectors
- Vector arithmetic
- Simple patterned vectors
- Missing values and other special values
- Character vectors
- Factors
- More on extracting elements from vectors
- Matrices and arrays
- Data frames
- Dates and times
Import and Export data in R
Importing data in to R
- CSV File
- Excel File
- Import data from text table
- SAS and SPSS datasets
Exporting Data from R
- CSV File
- Text Table
- Excel File
- SAS dataset
Merge / Join
- Inner Join
- Left Join
- Right Join
- Full Join
- Anti-Join
- Semi Join
Programming statistical graphics
High-level plots
- Bar charts and dot charts
- Pie charts
- Histograms
- Box plots
- Scatterplots
- QQ plots
- Density Plot
Choosing a high-level graphic
Low-level graphics functions
- The plotting region and margins
- Adding to plots
- Setting graphical parameters
Programming with R
Flow control
- The for() loop
- The if() statement
- The while() loop
- The repeat loop, and the break and next statements
- Apply
- Sapply
- Lapply
Managing complexity through functions What are functions?
- Scope of variables
Data Manipulation Techniques using R programming
Data in R
- Modes and Classes
- Data Storage in R
- Testing for Modes and Classes
- Structure of R Objects
- Conversion of Objects
- Missing Values
- Working with Missing Values
Reading and Writing Data
- Reading Vectors and Matrices
- Data Frames: read.table
- Comma- and Tab-Delimited Input Files
- Fixed-Width Input Files
- Extracting Data from R Objects
- Connections
- Reading Large Data Files
- Generating Data
- Sequences
- Random Numbers
- Permutations
- Random Permutations
- Enumerating All Permutations
- Working with Sequences Vs Spreadsheets
- The RODBC Package on Windows
- The gdata Package (All Platforms)
- Saving and Loading R Data Objects
- Working with Binary Files
- Writing R Objects to Files in ASCII Format
- The write Function
- The write.table function
- Reading Data from Other Programs
Dates
- Date
- The chron Package
- POSIX Classes
- Working with Dates
- Time Intervals
- Time Sequences
- Current time
- Present date
Factors
- Using Factors
- Numeric Factors Vs Manipulating Factors
- Creating Factors from Continuous Variables
Subscripting
- Basics of Subscripting
- Numeric Subscripts
- Character Subscripts
- Logical Subscripts
- Subscripting Matrices and Arrays
- Specialized Functions for Matrices
- Lists
- Subscripting Data Frames
Character Manipulation
- Basics of Character Data
- Displaying and Concatenating Character
- Working with Parts of Character Values
- Regular Expressions in R
- Basics of Regular Expressions
- Breaking Apart Character Values
- Using Regular Expressions in R
- Substitutions and Tagging
Reshaping Data
- Modifying Data Frame Variables
- Recoding Variables
- The recode Function
- Reshaping Data Frames
- The reshape Package
- Combining Data Frames
Data Manipulation
- Random Selection of rows and columns
- Summarization
- Sort, Arrange
- Group by
- Filter
Missing Value and Outlier
- Identify Missing values
- Impute missing values
- Identify Outliers
- Capping outliers