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![Example
Billionaires per Country
44
Country
Billionaires per 10M
Residents Per Capita Income
Number of
Billionaires
United States 54.7 $ 54,600 1764
China 1.5 $ 12,880 213
Germany 12.5 $ 45,888 103
India 0.7 $ 5,855 90
Russia 6.2 $ 24,850 88
Mexico 1.2 $ 17,881 15
[CELLRANGE]
[CELLRANGE]
[CELLRANGE]
[CELLRANGE]
[CELLRANGE]
[CELLRANGE]
$(10,000)
$-
$10,000
$20,000
$30,000
$40,000
$50,000
$60,000
$70,000
-10 0 10 20 30 40 50 60 70
Per
Capita
Income
Billionaires per 10 million residents
Billionaires per Country
The size of each bubble is
proportionate to the number of
billionaires in that country](https://image.slidesharecdn.com/noteschapter3-221217022431-35851369/85/Notes-Chapter-3-pptx-44-320.jpg)
Notes Chapter 3.pptx
- 1. MBA 643 Dr DanielleMorin Fall 2022 CHAPTER 3 DATA VISUALIZATION
- 2. Introduction Data visualization involves: ◦Creating a summary table for the data ◦ Generating charts to help interpret, analyze, and learn from the data Uses of data visualization: ◦ Helpful for identifying data errors ◦ Reduces the size of your data set by highlighting important relationships and trends in the data 2
- 3. Overview of Data Visualization EFFECTIVEDESIGN TECHNIQUES 3
- 4. Overview of DataVisualization Data-ink ratio: Measures the proportion of “data-ink” to the total amount of ink used in a table or chart ◦ Edward R. Tufte first described the data-ink ratio ◦ Helpful for creating effective tables and charts for data visualization ◦ Data-ink: Ink used in a table or chart that is necessary to convey the meaning of the data to the audience ◦ Non-data-ink: Ink used in a table or chart that serves no useful purpose in conveying the data to the audience 4 https://www.youtube.com/watch?v=JIMUzJzqaA8
- 5. Example Low Data-Ink RatioTable / Low Data-Ink Ratio Chart 5 Scarf Sales by Day Day Sales Days Sales 1 150 11 170 2 170 12 160 3 140 13 290 4 150 14 200 5 180 15 210 6 180 16 110 7 210 17 90 8 230 18 140 9 140 19 150 10 200 20 230 0 50 100 150 200 250 300 350 0 5 10 15 20 25 Scarf Sales per day Sales What is not necessary?
- 6. Example Increasing Data-Ink Ratioin Table and Chart 6 Scarf Sales by Day Day Sales Days Sales 1 150 11 170 2 170 12 160 3 140 13 290 4 150 14 200 5 180 15 210 6 180 16 110 7 210 17 90 8 230 18 140 9 140 19 150 10 200 20 230 HOW? Remove gridlines Add labels to axis Remove unnecessary lines and labels
- 7. Tables TABLE DESIGN PRINCIPLES CROSSTABULATION PIVOTTABLES IN EXCEL RECOMMENDED PIVOT TABLE IN EXCEL
- 8. Tables Tables should beused when: 1. The reader needs to refer to specific numerical values 2. The reader needs to make precise comparisons between different values and not just relative comparisons 3. The values being displayed have different units or very different magnitudes 8
- 9. Example Exact Values forCosts and Revenues by Month and corresponding line chart 9 Month 1 2 3 4 5 6 total Costs($) 48,123 56,458 64,125 52,158 54,718 50,985 326,567 Revenues($) 64,124 66,128 67,125 48,178 51,785 55,687 353,027 0 20,000 40,000 60,000 80,000 1 2 3 4 5 6 Costs and Revenues ($) Month Costs and Revenues by Month Costs($) Revenues($)
- 10. Example Exact Values forCosts and Revenues by Month and corresponding line chart 10 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 1 2 3 4 5 6 Costs and Revenues ($) Month Costs and Revenues by Month Costs($) Revenues($)
- 11. Example Exact Values forCosts and Revenues by Month and corresponding line chart 11 1 2 3 4 5 6 Costs($) 48,123 56,458 64,125 52,158 54,718 50,985 Revenues($) 64,124 66,128 67,125 48,178 51,785 55,687 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 Costs and Revenues ($) Month Costs and Revenues by Month Costs($) Revenues($)
- 12. Tables Principles ◦ Data-InkRatio ◦ Avoid using vertical lines in a table unless they are necessary for clarity ◦ Horizontal lines are generally necessary only for separating column titles from data values or when indicating that a calculation has taken place 12
- 13. Comparing Different TableDesigns 13 Which one is better?
- 14. Example Table of Revenuesby Location for 12 Months of Data 14
- 15. Example Table of Revenuesby Location for 12 Months of Data 15 1. Column of numbers should be right aligned 2. Always use the same number of decimals 3. Use decimals only when necessary 4. Large numbers should be adjusted with units of $1000 5. Left align text values in columns If we are interested in showing differences of Revenues between locations, the rows instead of the columns should have different shades of colours.
- 16. Tables Crosstabulation: A usefultype of table for describing data of two variables PivotTable: A crosstabulation in Microsoft Excel 16
- 17. Example How to analysisthis data set? Quality Rating and Meal Price for 300 Los Angeles Restaurants 17
- 18. Count of RestaurantColumn Labels Row Labels 10 1 1 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 40 41 42 43 44 45 46 47 48Grand Total Excellent 1 1 2 1 1 2 1 1 1 3 2 4 3 5 3 2 3 4 2 2 4 4 2 1 2 2 3 2 2 66 Good 64 3 3 2 4 4 5 5 6 10 1 3 5 1 3 4 5 5 3 1 1 84 Very Good 14 3 5 6 1 5 3 3 3 9 9 4 6 5 9 4 8 10 7 5 6 6 5 5 2 4 6 1 2 1 1 1 150 Grand Total 78 6 9 8 5 9 9 8 9 21 11 8 13 7 13 9 16 17 3 11 8 11 10 7 8 6 7 8 5 4 4 1 3 3 3 2 3 300 First step: Pivot Table: Rows = Quality Rating Columns = Meal Price Values = Count of Restaurants Count of Restaurant Column Labels Row Labels 10-19 20-29 30-39 40-49 Grand Total Excellent 2 14 28 22 66 Good 42 40 2 84 Very Good 34 64 46 6 150 Grand Total 78 118 76 28 300 Right click on a cell that contains a meal price column label / select Group / Starting at : 10, Ending at 49, By 10
- 19. Right click on Excellent/Move / Move “Excellent” to End Count of Restaurant Meal Price Quality Rating 10-19 20-29 30-39 40-49 Grand Total Good 42 40 2 84 Very Good 34 64 46 6 150 Excellent 2 14 28 22 66 Grand Total 78 118 76 28 300 Count of Restaurant Meal Price Quality Rating 10-19 20-29 30-39 40-49 Grand Total Good 14.00% 13.33% 0.67% 0.00% 28.00% Very Good 11.33% 21.33% 15.33% 2.00% 50.00% Excellent 0.67% 4.67% 9.33% 7.33% 22.00% Grand Total 26.00% 39.33% 25.33% 9.33% 100.00% Select Field Settings / Show values as / % of Grand Total Percent Frequency Distribution
- 20. Interpretation What is themost popular combination of quality Rating and Meal Price? How many restaurants have excellent rating and a meal price in the $10–19 range? What is the percentage of restaurants with excellent quality rating? 20 Count of Restaurant Meal Price Quality Rating 10-19 20-29 30-39 40-49 Grand Total Good 42 40 2 84 Very Good 34 64 46 6 150 Excellent 2 14 28 22 66 Grand Total 78 118 76 28 300
- 21. Example What is theaverage Waiting time per Meal Price and Quality rating? 21 In the Pivot Table, instead of asking for the Count of Restaurants, we ask for the average of Waiting Time What can we conclude? Average of Wait Time (min) Meal price Quality Rating 10-19 20-29 30-39 40-49 Grand Total Good 2.57 2.45 0.50 2.46 Very Good 12.65 12.56 12.04 10.00 12.32 Excellent 25.50 29.07 34.00 32.27 32.12 Grand Total 7.55 11.09 19.83 27.50 13.92
- 22. Charts SCATTER CHARTS RECOMMENDED CHARTSIN EXCEL LINE CHARTS BAR CHARTS AND COLUMN CHARTS BUBBLE CHARTS HEAT MAPS PIVOTCHARTS IN EXCEL
- 23. Charts Charts (or graphs):Visual methods of displaying data Scatter chart: Graphical presentation of the relationship between two quantitative variables Trendline: A line that provides an approximation of the relationship between the variables Line chart: A line connects the points in the chart ◦ Useful for time series data collected over a period of time (minutes, hours, days, years, etc.) 23
- 24. Example Number of Commercialsand Sales of Electronics 24 Week No. of Commercials Sales Volume 1 2 50 2 5 57 3 1 41 4 3 54 5 4 54 6 1 38 7 5 63 8 3 48 9 4 59 10 2 46 What is the independent variable? What is the dependent variable? The manager wants to know whether a linear relationship exists between Number of commercials and Sales on the following week.
- 25. Example Number of Commercialsand Sales of Electronics 25 Week No. of Commercials X Sales Volume ($100) Y 1 2 50 2 5 57 3 1 41 4 3 54 5 4 54 6 1 38 7 5 63 8 3 48 9 4 59 10 2 46
- 26. Example Number of Commercialsand Sales of Electronics 26 0 10 20 30 40 50 60 70 0 1 2 3 4 5 6 Sales Volume ($100) Number of Commercials Sales Volume by No. of Commercials 0 10 20 30 40 50 60 70 0 1 2 3 4 5 6 Sales Volume ($100) Number of Commercials Sales Volume by No. of Commercials Insert Scatter(X,Y) Add a Trend line that provides an approximation of the relationship between the variables Y =4.95X + 36.15 𝑅2 = 0.8658 𝑹 = 𝑹𝟐 = 𝟎. 𝟖𝟔𝟓𝟖 = 𝟎. 𝟗𝟑𝟎𝟓
- 27. Example Number of Commercialsand Sales of Electronics 27 0 10 20 30 40 50 60 70 0 1 2 3 4 5 6 Sales Volume ($100) Number of Commercials Sales Volume by No. of Commercials Interpret Calculate the correlation between Sales and No. of Commercials? R = 0.93
- 28. Example Monthly Sales Dataof Air Compressors at Kirkland Industries 28 Month Sales ($100s) Jan 135 Feb 145 Mar 175 Apr 180 May 160 Jun 135 Jul 210 Aug 175 Sep 160 Oct 120 Nov 115 Dec 120 What can we say about the monthly sales?
- 29. Scatter Chart andLine Chart for Monthly Sales Data 29 0 50 100 150 200 250 Sales ($100) Months Line Chart for Monthly Sales ($100s) 0 50 100 150 200 250 0 5 10 15 Sales ($100) Months Scatter Chart for Monthly Sales ($100s)
- 30. 30 Sales ($100s) Month NorthSouth Jan 95 40 Feb 100 45 Mar 120 55 Apr 115 65 May 100 60 Jun 85 50 Jul 135 75 Aug 110 65 Sep 100 60 Oct 50 70 Nov 40 75 Dec 40 80 Example Regional Monthly Sales Data of Air Compressors What can we say about the regional monthly sales?
- 31. Line Chart ofRegional Sales Data 31 0 50 100 150 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Sales (100$) Months Line Chart of Regional Data Sales North South
- 32. Sparkline ◦ Minimalist typeof line chart that can be placed directly into a cell in Excel ◦ Contain no axes; they display only the line for the data ◦ Take up very little space and they can be effectively used to provide information on overall trends for time series data 32
- 33. Sparklines for theRegional Sales Data 33
- 34.
- 35. Charts Bar Charts: Usehorizontal bars to display the magnitude of the quantitative variable Column Charts: Use vertical bars to display the magnitude of the quantitative variable Bar and column charts are very helpful in making comparisons between categorical variables 35
- 36. Example Manager Accounts Managed Davis 24 Edwards 11 Francois28 Gentry 37 Jones 15 Lopez 29 Smith 21 Williams 6
- 37. 24 11 28 37 15 29 21 6 0 10 20 30 40 Accounts managed Managers Bar Chart ofAccounts Managed 24 11 28 37 15 29 21 6 0 10 20 30 40 Davis Edwards Francois Gentry Jones Lopez Smith Williams Accounts managed Managers Bar Chart of Accounts Managed
- 38. Example Manager Accounts Managed Davis 24 Edwards 11 Francois28 Gentry 37 Jones 15 Lopez 29 Smith 21 Williams 6 Manager Accounts Managed Gentry 37 Lopez 29 Francois 28 Davis 24 Smith 21 Jones 15 Edwards 11 Williams 6
- 39. 6 11 15 21 24 28 29 37 0 5 1015 20 25 30 35 40 Williams Edwards Jones Smith Davis Francois Lopez Gentry Accounts managed Managers Bar Chart of Accounts Managed
- 40. Charts Pie charts: Commonform of chart used to compare categorical data Bubble chart: ◦ Graphical means of visualizing three variables in a two- dimensional graph ◦ Sometimes a preferred alternative to a 3-D graph Heat map: A two-dimensional graphical representation of data that uses different shades of color to indicate magnitude 40
- 41. Example Pie Chart ofAccounts Managed 41 37 29 28 24 21 15 11 6 Accounts Managed Gentry Lopez Francois Davis Smith Jones Edwards
- 42. Example Billionaires per Country 42 Country Billionairesper 10M Residents Per Capita Income Number of Billionaires United States 54.7 $ 54,600 1764 China 1.5 $ 12,880 213 Germany 12.5 $ 45,888 103 India 0.7 $ 5,855 90 Russia 6.2 $ 24,850 88 Mexico 1.2 $ 17,881 15
- 43. Example Billionaires per Country 43 Country Billionairesper 10M Residents Per Capita Income Number of Billionaires United States 54.7 $ 54,600 1764 China 1.5 $ 12,880 213 Germany 12.5 $ 45,888 103 India 0.7 $ 5,855 90 Russia 6.2 $ 24,850 88 Mexico 1.2 $ 17,881 15 X Y Bubble size Bubble label
- 44. Example Billionaires per Country 44 Country Billionairesper 10M Residents Per Capita Income Number of Billionaires United States 54.7 $ 54,600 1764 China 1.5 $ 12,880 213 Germany 12.5 $ 45,888 103 India 0.7 $ 5,855 90 Russia 6.2 $ 24,850 88 Mexico 1.2 $ 17,881 15 [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] $(10,000) $- $10,000 $20,000 $30,000 $40,000 $50,000 $60,000 $70,000 -10 0 10 20 30 40 50 60 70 Per Capita Income Billionaires per 10 million residents Billionaires per Country The size of each bubble is proportionate to the number of billionaires in that country
- 45. Example Heat Map 45 A Heatmap is a two dimensional graphical representation of data that uses different shapes of color to indicate magnitude.
- 46. Example Heat Map andSparklines for Same-Store Sales Data 46 Same-store Sales is a measure used often in the retail industry to measure trends in sales JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC St. Louis -2% -1% -1% 0% 2% 4% 3% 5% 6% 7% 8% 8% Phoenix 5% 4% 4% 2% 2% -2% -5% -8% -6% -5% -7% -8% Albany -5% -6% -4% -5% -2% -5% -5% -3% -1% -2% -1% -2% Austin 16% 15% 15% 16% 18% 17% 14% 15% 16% 19% 18% 16% Cincinnati -9% -6% -7% -3% 3% 6% 8% 11% 10% 11% 13% 11% San Francisco 2% 4% 5% 8% 4% 2% 4% 3% 1% -1% 1% 2% Seattle 7% 7% 8% 7% 5% 4% 2% 0% -2% -4% -6% -5% Chicago 5% 3% 2% 6% 8% 7% 8% 5% 8% 10% 9% 8% Atlanta 12% 14% 13% 17% 12% 11% 8% 7% 7% 8% 5% 3% Miami 2% 3% 0% 1% -1% -4% -6% -8% -11% -13% -11% -10% Minneapolis -6% -6% -8% -5% -6% -5% -5% -7% -5% -2% -1% -2% Denver 5% 4% 1% 1% 2% 3% 1% -1% 0% 1% 2% 3% Salt Lake City 7% 7% 7% 13% 12% 8% 5% 9% 10% 9% 7% 6% Raleigh 4% 2% 0% 5% 4% 3% 5% 5% 9% 11% 8% 6% Boston -5% -5% -3% 4% -5% -4% -3% -1% 1% 2% 3% 5% Pittsburgh -6% -6% -4% -5% -3% -3% -1% -2% -2% -1% -2% -1%
- 47. Example Heat Map andSparklines for Same-Store Sales Data 48 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC St. Louis -2% -1% -1% 0% 2% 4% 3% 5% 6% 7% 8% 8% Phoenix 5% 4% 4% 2% 2% -2% -5% -8% -6% -5% -7% -8% Albany -5% -6% -4% -5% -2% -5% -5% -3% -1% -2% -1% -2% Austin 16% 15% 15% 16% 18% 17% 14% 15% 16% 19% 18% 16% Cincinnati -9% -6% -7% -3% 3% 6% 8% 11% 10% 11% 13% 11% San Francisco 2% 4% 5% 8% 4% 2% 4% 3% 1% -1% 1% 2% Seattle 7% 7% 8% 7% 5% 4% 2% 0% -2% -4% -6% -5% Chicago 5% 3% 2% 6% 8% 7% 8% 5% 8% 10% 9% 8% Atlanta 12% 14% 13% 17% 12% 11% 8% 7% 7% 8% 5% 3% Miami 2% 3% 0% 1% -1% -4% -6% -8% -11% -13% -11% -10% Minneapolis -6% -6% -8% -5% -6% -5% -5% -7% -5% -2% -1% -2% Denver 5% 4% 1% 1% 2% 3% 1% -1% 0% 1% 2% 3% Salt Lake City 7% 7% 7% 13% 12% 8% 5% 9% 10% 9% 7% 6% Raleigh 4% 2% 0% 5% 4% 3% 5% 5% 9% 11% 8% 6% Boston -5% -5% -3% 4% -5% -4% -3% -1% 1% 2% 3% 5% Pittsburgh -6% -6% -4% -5% -3% -3% -1% -2% -2% -1% -2% -1%
- 48. Additional Charts ◦ Stackedcolumn chart: Allows the reader to compare the relative values of quantitative variables for the same category in a bar chart ◦ Clustered column (or bar) chart: An alternative chart to stacked column chart for comparing quantitative variables ◦ Scatter chart matrix: Useful chart for displaying multiple variables 49 NOTE Stacked column and bar charts should be used only when comparing a few quantitative variables and when there are large differences in the relative values of the quantitative variables within the category.
- 49. Example Stacked-Column Chart forRegional Sales Data 51 0 50 100 150 200 250 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Sales ($100) Months Stacked Column Chart for Regional Sales South North Although Stacked- Column Chart allow the reader to compare the relative values of quantitative variables for the same category in a bar chart, however they suffer from the same difficulty perceiving small differences in areas.
- 50. Example Clustered-Column Chart forRegional Sales Data 52 The Clustered- Column Chart is superior to the Stacked-Column Chart for comparing a small number quantitative variables. 0 20 40 60 80 100 120 140 160 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Sales ($100) Months Clurtered Column Chart for Regional Sales North South
- 51. Compare Stacked-, Clustered-, andMultiple-Column Charts for the Regional Sales 53 When comparing many quantitative variables, using multiple charts can often be superior even if each chart must be made smaller. Stacked-column and stacked-bar charts should be used only when comparing a few quantitative variables and when there are large differences in the relative values of the quantitative variables within the category.
- 52. Example Data for NewYork City 55 Subboroughs on 54 Area Median Monthy Rent ($) Percentage College Graduates (%) Poverty Rate (%) Travel Time (min) Astoria 1106 36.8 15.9 35.4 Bay Ridge 1082 34.3 15.6 41.9 Bayside/Little Neck 1243 41.3 7.6 40.6 Bedford Stuyvesant 822 21.0 34.2 40.5 Bensonhurst 876 17.7 14.4 44.0 Borough Park 980 26.0 27.6 35.3 Brooklyn Heights/Fort Greene 1086 55.3 17.4 34.5 Brownsville/Ocean Hill 714 11.6 36.0 40.3 Bushwick 945 13.3 33.5 35.5 Central Harlem 665 30.6 27.1 25.0 Chelsea/Clinton/Midtown 1624 66.1 12.7 43.7 Coney Island 786 27.2 20.0 46.3 East Flatbush 940 18.4 11.7 33.2 East Harlem 677 23.7 30.0 44.2 East New York/Starrett City 890 13.7 29.2 43.9 Elmhurst/Corona 1121 21.8 22.3 41.1 Flatbush 931 28.3 25.1 43.9 Flatlands/Canarsie 1052 26.6 9.3 42.0 Flushing/Whitestone 1170 32.5 11.4 23.4 Greenwich Village/Financial District 1965 78.3 7.9 44.0 Highbridge/South Concourse 781 11.2 31.4 44.6 Hillcrest/Fresh Meadows 1138 39.6 12.9 41.6 Jackson Heights 1114 19.8 16.0 47.3 Jamaica 980 19.8 12.7 42.8 Kingsbridge Heights/Moshulu 860 16.0 35.0 31.6 Lower East Side/Chinatown 821 34.2 25.9 39.0 Middle Village/Ridgewood 1078 20.1 12.1 39.7 … … …. … … • Median Monthly Rent($) • Percentage College Graduates (%) • Poverty Rate (%) • Travel Time (min)
- 53. A scatter-chart matrix allowsthe reader to easily see the relationships among multiple variables. Each scatter chart in the matrix is created in the same manner as for creating a single scatter chart. Each column and each row in the scatter-chart matrix corresponds to one categorical variable Scatter-Chart Matrix cannot be done in Excel. The Excel add-in Frontline Solver is required Data Mining- Explore- Chart Wizart – ScatterPlot Matrix % graduate Poverty Rate
- 54. PivotCharts in Excel PivotChartare used to summarize and analyze data with both a crosstabulation and charting, Excel pairs PivotCharts with PivotTables 56
- 55. Example PivotTable and PivotChartfor the Restaurant Data 57 Restaurant Quality Rating Meal Price ($) Wait Time (min) 1 Good 18 5 2 Very Good 22 6 3 Good 28 1 4 Excellent 38 74 5 Very Good 33 6 6 Good 28 5 7 Very Good 19 11 … … A sample of 300 restaurants was collected and the following variables were studied: Quality Rating Meal Price ($) Wait Time (min)
- 56. Example PivotTable and PivotChartfor the Restaurant Data 58 Average of Wait Time (min) Column Labels Row Labels 10-19 20- 29 30- 39 40- 49 Grand Total Good 2.6 2.5 0.5 2.5 Very Good 12.6 12.6 12.0 10.0 12.3 Excellent 25.5 29.1 34.0 32.3 32.1 Grand Total 7.6 11.1 19.8 27.5 13.9
- 57. Advanced Data Visualization ADVANCED CHARTS GEOGRAPHICINFORMATION SYSTEMS CHARTS
- 58. Advanced Data Visualization Parallel-coordinatesplot: Chart for examining data with more than two variables ◦ Includes a different vertical axis for each variable ◦ Each observation is represented by drawing a line on the parallel coordinates plot connecting each vertical axis ◦ The height of the line on each vertical axis represents the value taken by that observation for the variable corresponding to the vertical axis Treemap: Useful for visualizing hierarchical data along multiple dimensions 61
- 59. Example Plot for BaseballData 62 Position HR SB AVG 1B 39 4 0.248 1B 38 1 0.299 1B 37 9 0.299 1B 33 1 0.253 1B 31 2 0.301 1B 31 1 0.3 1B 31 2 0.303 1B 29 8 0.309 1B 28 2 0.225 1B 27 1 0.338 2B 32 30 0.255 2B 21 26 0.307 2B 2 22 0.303 2B 0 21 0.255 2B 8 21 0.246 2B 7 19 0.246 2B 21 17 0.236 2B 21 16 0.222 2B 2 15 0.26 2B 7 14 0.248 Data on 20 Baseball players where 10 play first base (1B) (in Blue) and 10 play second base (2B). (in red) HR : Number of Home Runs SB: Number of Stolen Bases AVG: Batting Average
- 60. Example Plot for BaseballData 63 Data mining – Explore – Chart Wizart – Parallel Coordinates – Select HR, SB and AVG - Colors Blue : First Base Red : Second Base
- 61. Advanced Data Visualization ◦Geographic Information Systems (GIS): A system that merges maps and statistics to present data collected over different geographies ◦ Helps in interpreting data and observing patterns 64
- 62. Example GIS Chart forCincinnati Zoo Member Data 65
- 63. Data Dashboards PRINCIPLES OFEFFECTIVE DATA DASHBOARDS APPLICATION OF DATA DASHBOARDS
- 64. Data Dashboards Data dashboard:Data visualization tool that illustrates multiple metrics and automatically updates these metrics as new data become available Key performance indicators (KPIs) in dashboards: ◦ Automobile dashboard: Current speed, Fuel level, and oil pressure ◦ Business dashboard: Financial position, inventory on hand, customer service metrics 67
- 65. Data Dashboards Principles ofEffective Data Dashboards ◦ Should provide timely summary information on KPIs that are important to the user ◦ Should present all KPIs as a single screen that a user can quickly scan to understand the business’s current state of operations ◦ The KPIs displayed in the data dashboard should convey meaning to its user and be related to the decisions the user makes ◦ A data dashboard should call attention to unusual measures that may require attention ◦ Color should be used to call attention to specific values to differentiate categorical variables, but the use of color should be restrained 68
- 66. Example Data Dashboard forthe Grogan Oil Information Technology Call Center 69