Data Visualization with #KCDC

Transcription

1 Data Visualization with #KCDC

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11 Overview Introduction to R Intro to Data Visualization Types of Data Visualizations Visualizing One Variable Visualizing Two Variables Visualizing Many Variables Visualizing Other Types of Data Beyond the Basics

12 About Me Independent software consultant Education B.S. in Computer Science B.A. in Philosophy Community Pluralsight Author ASPInsider Public Speaker Open-Source Software

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14 Introduction to R

15 What is R? Open source Language and environment Numerical and graphical analysis Cross platform

16 What is R? Active development Large user community Modular and extensible extensions

17 FREE

18 FREE

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23 Code Demo

24 Intro to Data Visualization

25 Data Visualization Visual data representation For human pattern recognition Map dimensions to visual

26 Data Visualization ID Date Customer Product Quantity John Pizza John Soda Jill Salad Jill Milk Miko Pizza Miko Soda Sam Pizza Sam Milk 1

27 Statistical Terms ID Date Customer Product Quantity Observations Variables Qualitative variable Quantitative variable John Pizza John Soda Jill Salad Jill Milk Miko Pizza Miko Soda Sam Pizza Sam Milk 1

28 Number of Variables Types of Data Visualizations One Categorical Variable One Numeric Variable Number of variables Type of variable(s) Two Categorical Variables Categorical & Numeric Variable Two Numeric Variables Many Variables Type of Variable(s)

29 Plotting Systems in R Base Lattice ggplot2

30 Code Demo

31 Visualizing One Variable

32 Number of Variables Visualizing One Variable One Categorical Variable One Numeric Variable Two Categorical Variables Categorical & Numeric Variable Two Numeric Variables Many Variables Type of Variable(s)

33 Visualizing One Categorical Variable Frequency Proportion

34 Visualizing One Numeric Variable Location Spread Shape

35 Open Movies Database Title Year Rating Runtime (minutes) Movies Genre Critic Score Box Office Awards Distribution The Whole Nine Yards 2000 R 98 Comedy 45% $57.3M No Domestic Cirque du Soleil 2000 G 39 Family 45% $13.4M Yes Domestic Gladiator 2000 R 155 Action 76% $187.3M Yes International Dinosaur 2000 PG 82 Family 65% $135.6M Yes Domestic Big Momma's House 2000 PG Comedy 30% $0.5M Yes International

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38 1. How does the count of movies compare by rating category? 2. What proportion of movies have won awards? 3. What does the distribution of movie runtimes look like?

39 Code Demo

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41 Visualizing Two Variables

42 Number of Variables Visualizing Two Variables One Categorical Variable One Numeric Variable Two Categorical Variables Categorical & Numeric Variable Two Numeric Variables Many Variables Type of Variable(s)

43 Visualizing Two Categorical Variables Movies by Genre and Rating Genre G PG PG-13 R Total Action Joint frequency Marginal frequency Relative frequency Adventure Animation Comedy Drama Family Total

44 Visualizing Two Categorical Variables Movies by Genre and Rating Genre G PG PG-13 R Total Action Joint frequency Marginal frequency Relative frequency Adventure Animation Comedy Drama Family Total

45 Visualizing Two Numeric Variables Relationship Correlation Distribution

46 Visualizing Two Numeric Variables Relationship Correlation Distribution

47 Visualizing Time Series Data Values over time Rate of change

48 Visualizing a Numeric Variable Grouped by a Categorical Variable Aggregate Grouped Comparison

49 1. How many award-winning movies by rating category? 2. How are runtime and boxoffice revenue related? 3. Has the average box-office revenue changed over time? 4. How does box office compare by rating category

50 Code Demo

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52 Visualizing Many Variables

53 Number of Variables Visualizing Many Variables One Categorical Variable One Numeric Variable Two Categorical Variables Categorical and Numeric Variable Two Numeric Variables Many Variables Type of Variable(s)

54 Faceting

55 Faceting Orientation Horizontal Vertical Wrapped

56 Faceting Base Lattice ggplot2

57 1. How many movies based on rating, award, and dist.? 2. How does box office compare across awards and rating? 3. How does critic score relate to box office by rating category? 4. How has box office revenue changed over time by rating? 5. How do runtime and critic score relate to box office?

58 Code Demo

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60 Visualizing Other Types of Data

61 Source: Nathan Yau (

62 1. What is the box office revenue for films by country? 2. What is the box office revenue by continent and country? 3. Which actors have acted most frequently with one another? 4. Which movie plot words are associated with revenue?

63 Code Demo

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65 Beyond the Basics

66 This is just the tip of the iceberg! This is just the tip of the iceberg!

67 Animating Data Visualizations

68 Building Interactive Data Visualizations

69 1. How have the top 10 studios grown over the past 15 years? 2. Allow me to explore the data to ask any question I might dream up on a random Tues. and I want it done today.

70 Code Demo

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72 Where to Go Next R website: R Studio: Revolutions: Flowing Data: R-Blogger: R-Seek:

73 My Website Articles Presentations Source Code Videos Workshops

74 Exploratory Data Analysis with R Beginning Data Visualization with R Multivariate Data Visualization with R Mastering Data Visualization with R

75 Conclusion

76 Conclusion Introduction to R Intro to Data Visualization Types of Data Visualizations Visualizing One Variable Visualizing Two Variables Visualizing Many Variables Visualizing Other Types of Data Beyond the Basics

77 Feedback Feedback is very important to me! One thing you liked? One thing I could improve?

78 Contact Info Matthew Renze Data Science Consultant Renze Consulting Website: Thank You! : )