Base R Programming
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Section 1: Getting Started
- Course Overview
- How to Get Queries Resolved
- Download Resources
- Installing R Studio
- R Studio walkthrough
Section 2: Data Concepts
- Datatypes
- Data Structures
Section 3: Vectors
- Vectorization
- Online Pizza Advertisement
- Create vector with a single element
- Create group of elements in a vector
- Use repetitions and sequence to create a vector fast
- Random numbers, rounding and sampling
- Formatting numbers
- Create subsets
- Handling Missing Values
- Binning
- Operations within a vector
- Operations between same size vectors
- Operations between different sized vectors
- Revenue impact of Ad-campaign
- Course Review
Section 4: Programming Basics
- Module Overview
- If and ifelse
- Making assignments within ifelse
- Checking existence
- Nested if-else
- For loops
- Writing smarter For loops
- Break while repeat
- Memory pre-allocation tactics
- Why Dates cant just be strings
- Date operations
- Working with lubridate and anytime
- Working with lubridate and anytime
Section 5: Lists in R
- Introduction to lists
- Named list, unlist and more
- Course Review
Section 6: Dataframe
- Introduction to Dataframe
- Creating Dataframe
- Visual editing
- Various dataframe operations
- Inspecting and Rownames
- Select, delete, subset
- Attributes and comments
- Saving dataframe to disk
- Native RDS files
- Handling CSV files
- Xlsx files
- SAS and Stata files
- R datasets, packages and public datasets
- Useful data summarization function
- Conditional filtering and missing values
- Matrix vs dataframe
- Joining operations for dataframes
- Pivot and frequency table
- Grouping and case problem solution
Section 7: Base Graphics
- Module Overview
- Base Graphics basics
- Scatterplot
- Adding plot components
- Legend
- Saving plot components and challenge
- Line plot with secondary Y axis
- Change Par settings
- Histogram and bar charts
- Box plot
- Dot plot and density plot
- Multiple plots and custom layouts
- Course Review
Section 8: R Core Programming
- Intro to stringr
- Sentences, punctuations, strings manipulations
- Writing effective functions
- Local and global namespace
- Writing effective functions
- Local and global namespace
- Debugging R code
- Error handling
- Apply Function
- lapply, sapply, vapply
- Mapply