An Introduction to Exploratory v5.3

Introducing new features and critical enhancements of Exploratory v5.3.

Transcript

1. Exploratory Seminar Exploratory v5.3
2. EXPLORATORY
3. Kan Nishida co-founder/CEO Exploratory Summary Beginning of 2016, launched Exploratory, Inc. to democratize Data Science. Prior to Exploratory, Kan was a director of product development at Oracle leading teams for building various Data Science products in areas including Machine Learning, BI, Data Visualization, Mobile Analytics, Big Data, etc. While at Oracle, Kan also provided training and consulting services to help organizations transform with data. @KanAugust Speaker
4. Mission Make Data Science Available for Everyone
5. Data Science is not just for Engineers and Statisticians. Exploratory makes it possible for Everyone to do Data Science. The Third Wave
6. First Wave Second Wave Third Wave Proprietary Open Source UI & Programming Programming 2016 2000 1976 Monetization Commoditization Democratization Statisticians Data Scientists Democratization of Data Science Algorithms Experience Tools Open Source UI & Automation Business Users Theme Users
7. Questions Communication (Dashboard, Note, Slides) Data Access Data Wrangling Visualization Analytics (Statistics / Machine Learning) Exploratory Data Analysis
8. Exploratory v5.3
9. Questions Communication (Dashboard, Note, Slides) Data Access Data Wrangling Visualization Analytics (Statistics / Machine Learning)
10. Analytics • Test Mode Support for Statistical / Machine Learning Models • Cut Point for Binary Classification (TRUE/FALSE) • Updated Default Setting - Random Forest, Linear Regression, Logistic Regression • Prophet - Extra Regressor, Daily Seasonality, Multiplicative, Change Point Range • Power Analysis, Effect Size • Support for Wilcoxon Test and Kruskal-Wallis Test • GLM - Negative Binomial
11. Analytics • Test Mode Support for Statistical / Machine Learning Models • Cut Point for Binary Classification (TRUE/FALSE) • Updated Default Setting - Random Forest, Linear Regression, Logistic Regression • Prophet - Extra Regressor, Daily Seasonality, Multiplicative, Change Point Range • Power Analysis, Effect Size • Support for Wilcoxon Test and Kruskal-Wallis Test • GLM - Negative Binomial
12. Test Mode
16. Analytics • Test Mode Support for Statistical / Machine Learning Models • Cut Point for Binary Classification (TRUE/FALSE) • Updated Default Setting - Random Forest, Linear Regression, Logistic Regression • Prophet - Extra Regressor, Daily Seasonality, Multiplicative, Change Point Range • Power Analysis, Effect Size • Support for Wilcoxon Test and Kruskal-Wallis Test • GLM - Negative Binomial
17. Cut Point for Binary Classification (TRUE / FALSE)
18. Cut Pointɿ0.5
19. Cut Pointɿ0.8
20. Cut Pointɿ0.3
21. Analytics • Test Mode Support for Statistical / Machine Learning Models • Cut Point for Binary Classification (TRUE/FALSE) • Updated Default Setting - Random Forest, Linear Regression, Logistic Regression • Prophet - Extra Regressor, Daily Seasonality, Multiplicative, Change Point Range • Power Analysis, Effect Size • Support for Wilcoxon Test and Kruskal-Wallis Test • GLM - Negative Binomial
22. Random Forest: Boruta
23. Linear Regression: Variable Importance
24. Logistic Regression: Average Marginal Effect
25. Analytics • Test Mode Support for Statistical / Machine Learning Models • Cut Point for Binary Classification (TRUE/FALSE) • Updated Default Setting - Random Forest, Linear Regression, Logistic Regression • Prophet - Extra Regressor, Daily Seasonality, Multiplicative, Change Point • Power Analysis, Effect Size • Support for Wilcoxon Test and Kruskal-Wallis Test • GLM - Negative Binomial
26. Daily Seasonality
27. Change Point Period
28. Change Point : 0.8 (Default)
29. Change Point : 0.5
30. Additive vs. Multiplicative
31. Additive
32. Multiplicative
33. Additive
34. Multiplicative
35. Analytics • Test Mode Support for Statistical / Machine Learning Models • Cut Point for Binary Classification (TRUE/FALSE) • Updated Default Setting - Random Forest, Linear Regression, Logistic Regression • Prophet - Extra Regressor, Daily Seasonality, Multiplicative, Change Point Range • Power Analysis, Effect Size • Support for Wilcoxon Test and Kruskal-Wallis Test • GLM - Negative Binomial
36. Effect Size & Power
37. Power Analysis
38. Sample Size Estimation
39. Analytics • Test Mode Support for Statistical / Machine Learning Models • Cut Point for Binary Classification (TRUE/FALSE) • Updated Default Setting - Random Forest, Linear Regression, Logistic Regression • Prophet - Extra Regressor, Daily Seasonality, Multiplicative, Change Point Range • Power Analysis, Effect Size • Support for Wilcoxon Test and Kruskal-Wallis Test • GLM - Negative Binomial
40. Wilcoxon Test & Kruskal-Wallis Test
41. Analytics • Test Mode Support for Statistical / Machine Learning Models • Cut Point for Binary Classification (TRUE/FALSE) • Updated Default Setting - Random Forest, Linear Regression, Logistic Regression • Prophet - Extra Regressor, Daily Seasonality, Multiplicative, Change Point Range • Power Analysis, Effect Size • Support for Wilcoxon Test and Kruskal-Wallis Test • GLM - Negative Binomial
42. GLM - Negative Binomial
43. Chart • Categorization of Numeric Values (Binning) • Limit Values - Top / Bottom NɺCondition • Log, Absolute, Weekend • Pivot Table - Post Calculation, 30 Columns for Values • Re-order - X, Y, Legend
44. Chart • Categorization of Numeric Values (Binning) • Limit Values - Top / Bottom NɺCondition • Log, Absolute, Weekend • Pivot Table - Post Calculation, 30 Columns for Values • Re-order - X, Y, Legend
49. Categorize Numbers with Equal Width
50. Categorize Numeric Values for X-Axis & Color
51. Manually Set Cut Points
52. Add Label Text
53. Categorization with Outlier
54. Outlier by All Setting
55. Outlier by X-Axis Setting
56. Chart • Categorization of Numeric Values (Binning) • Limit Values - Top / Bottom NɺCondition • Log, Absolute, Weekend • Pivot Table - Post Calculation, 30 Columns for Values • Re-order - X, Y, Legend
57. Limit X-Axis Values
58. Top / Bottom N
59. You can use a column that is not included in the chart.
60. Condition
61. Slovenia’s Return Rate is 100%! But this could be because there is not many orders. The scale is between 0% and 100%.
62. Sure enough! Slovenia is gone. But it’s easier to see difference among other countries now. The scale is now between 0% and 11%.
63. Chart • Categorization of Numeric Values (Binning) • Limit Values - Top / Bottom NɺCondition • Log, Absolute, Weekend • Pivot Table - Post Calculation, 30 Columns for Values • Re-order - X, Y, Legend
64. Sales 64
65. log(Sales) 65
66. Pivot Table - More Values!
67. Pivot Table - Post Calculation for Grand Total
68. Data Wrangling
69. Data Wrangling • New UI - Summarize, Pivot, Rename • Updates for Merge Data Frames • Mode function • str_logical function • str_extract_inside function
70. Data Wrangling • New UI - Summarize, Pivot, Rename • Updates for Merge Data Frames • Mode function • str_logical function • str_extract_inside function
71. Summarize
72. Custom Function in Summarize
73. Pivot
74. Rename
75. Data Wrangling • New UI - Summarize, Pivot, Rename • Updates for Merge Data Frames • Mode function • str_logical function • str_extract_inside function
76. Merge - Bind Rows
79. Demo
80. Q & A
81. Contact Email kan@exploratory.io Home Page https://exploratory.io Twitter @KanAugust Online Seminar https://exploratory.io/online-seminar