Data visualization

1. EDA Visualization
before building model
Orozco Hsu
2023-10-31
1

2. About me
• Education
• NCU (MIS)、NCCU (CS)
• Work Experience
• Telecom big data Innovation
• AI projects
• Retail marketing technology
• User Group
• TW Spark User Group
• TW Hadoop User Group
• Taiwan Data Engineer Association Director
• Research
• Big Data/ ML/ AIOT/ AI Columnist
2

3. Tutorial
Content
3
Iris dataset summary
EDA and visualization
Homework

4. Code
• Download materials:
• https://drive.google.com/drive/folders/1Kaneenrtd2P2IWbo-
PhMd3b6NvtT5FOc?usp=sharing
4

5. Table
• Load dataset
• Iirs.tab
5

6. The most recommend dataset
• Where the independent variables are numerical and the dependent
variable is categorical
• The advantage of such a dataset also lies in its ease of clustering
• The preferable data type for the dependent variable is binary,
meaning it is either 'YES' or ‘NO
• When the number of independent variables exceeds two or more, the
accuracy will decrease
• The most commonly used algorithm is logistic regression
6

7. Table pivot
7

8. Rank
8

9. Correlations
9

10. Scatter plot
10

11. Distribution
11

12. Box plot
12

13. Feature Statistics
13

14. Homework
• Change dataset, the numeric target feature
• Please explain the data visualization
• housing.tab
14