Table of Contents

1. Introduction to data science
2. Installing R, RStudio, R Markdown, and R in JupyterLab
3. GitHub and Git basics
4. {swirl} interactive sessions
   4.1. Basic Building Blocks
   4.2. Workspace and Files
   4.3. Sequences of Numbers
   4.4. Vectors
   4.5. Missing Values
   4.6. Subsetting Vectors
   4.7. Matrices and Data Frames
   4.8. Logic
   4.9. Functions
   4.10. lapply and sapply
   4.11. vapply and tapply
   4.12. Looking at Data
   4.13. Simulation
   4.14. Dates and Times
   4.15. Base Graphics
   4.16. Manipulating Data with dplyr
   4.17. Grouping and Chaining with dplyr
   4.18. Tidying Data with tidyr
   4.19. Principles of Analytic Graphs
   4.20. Exploratory Graphs
   4.21. Graphics Devices in R
   4.22. Plotting Systems
   4.23. Base Plotting System
   4.24. Lattice Plotting System
   4.25. Working with Colors
   4.26. GGPlot2 Part1
   4.27. GGPlot2 Part2
   4.28. GGPlot2 Extras
   4.29. Hierarchical Clustering
   4.30. K Means Clustering
   4.31. Statistical Inference - Introduction
5. R programming
   5.1. COVID-19 data
   5.2. Air Pollution data
   5.3. Lexical Scoping
6. Data Preperation
   6.1. Data cleaning and tydying
   6.2. Data Codebook

... more to come soon

Last updated 2020-05-26 15:46:53.947407 IST