Exploratory data analysis
- 1. Exploratory Data Analysis By : Vishwas Narayan
- 2. Principles of Analytic Graphics Principle 1 : Show comparison Principle 2 : Show causality,mechanism,explanation.systematic structure Principle 3 : Show multivariate data Principle 4 : Integration Of the evidence Principle 5 : Describe and document the evidences with the appropriate labels,scales,sources etc Principle 6 : Content is king
- 3. Graphs ● To understand the data property ● To find patterns ● To suggest modeling strategy ● To “debug” analysis
- 4. Characteristics of the exploratory data ● They are made quickly ● A large number can be made ● The goal is for the personal understanding ● Axes/legends are generally cleaned up(later) ● Color and the size are the primary information
- 6. Two Dimensional Plots Multiple or the overlaid plots Scatter plots Smooth scatter plots
- 7. > 2 dimensional plots Co-plots Spinning plots Use of the color,size
- 8. Base plotting system test ,lines,points,axis These will be very convenient Difficult to translate Plot is just a series of the command
- 9. Lattice system The plots are created with the specific function Spacing and the margins are automatic only parameters(a lot in number) is to be given here. Panel plot are the different levels of the third variable.
- 10. The ggplot2 system Splits the difference between base and the lattice in the number of ways Automatically deals with the spacing,text,titles but also allows you to annotate adding to a plot Superficial similarity to lattice but generally easier/more intuitive to use
- 12. Today cost is the key
- 16. Shap Framework
- 17. Jmeter tool
- 18. Train Test Scree Plots
- 21. What is Data Wrangling? What you just did now is Data Wrangling.
- 23. Lattice data system behavior
Editor's Notes
- #3: https://simplystatistics.org/