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Visualizing Tabular Data

Visualizing Tabular Data. CS 4390/5390 Data Visualization Shirley Moore, Instructor September 29, 2014. Image Credits. All images from Munzner Chapter 7 unless otherwise noted. Tabular Data. Large classes of datasets can be characterized in the form of tables.

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Visualizing Tabular Data

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  1. Visualizing Tabular Data CS 4390/5390 Data Visualization Shirley Moore, Instructor September 29, 2014

  2. Image Credits • All images from Munzner Chapter 7 unless otherwise noted.

  3. Tabular Data • Large classes of datasets can be characterized in the form of tables. • e.g., relational databases • General form is a matrix of key attribute(s) in one or more dimensions and associated value attribute(s) in the remaining dimensions. • May have linked tables where value attribute in one table is key attribute in another • Layout and visualization of high dimensional tablular data is a challenging vis research problem.

  4. Using the Spatial Channel

  5. Key vs. Value Attributes • Key • Unique index used to look up items in a table • Can be categorical or ordinal • Value The value of a cell in a table • Can be categorical, ordinal, or quantitative • Design choices for visually encoding a table depend on how many keys and how many attributes it has • Show only values: scatterplot • Show one key and one value: bar chart • Show two keys and one value: heat map • Show many keys and many values: recursively divide subspace into many regions

  6. Scatterplot

  7. Image credit: http://en.wikipedia.org/wiki/Scatter_plot

  8. Scatterplot with Negative Correlation Image credit: https://onlinecourses.science.psu.edu/stat414/book/export/html/262

  9. Scatterplot with Log Scaling

  10. Bar Chart

  11. Pie Chart

  12. Bar and Pie Chart Examples • Bar chart • http://bl.ocks.org/mbostock/3885705 • Pie chart • D3pie pie chart generator

  13. Stacked Bar Chart

  14. Stacked Bar Chart vs.Grouped Bar Chart • Stacked bar chart example: • http://bl.ocks.org/mbostock/3886208 • Grouped bar chart example: • http://bl.ocks.org/mbostock/3887051

  15. Line Chart

  16. Don’t use line chart for categorical data!

  17. Time Series Data – Area Chart vs. Lines Chart • Exercise: In less than one minute, draw the line showing the sales trend for East from the area chart on the next slide (image from http://vizwiz.blogspot.com/2012/10/stacked-area-chart-vs-line-chart-great.html ):

  18. East Sales Trend – How close were you?

  19. Lines with Total

  20. Normalized Stacked Bar Chart Example: http://bl.ocks.org/mbostock/3886394

  21. Streamgraph Mathematical algorithms minimize change in slope (“wiggle”) in individual series.

  22. Streamgraph Examples • Original paper by Byron and Wattenberg with Listening History example • http://www.leebyron.com/else/streamgraph/ • Movie Box Office Receipts NYTimes article • http://www.nytimes.com/interactive/2008/02/23/movies/20080223_REVENUE_GRAPHIC.html • Article discussing streamgraphs • http://www.visualisingdata.com/index.php/2010/08/making-sense-of-streamgraphs/

  23. Heatmap

  24. Heatmap with Hierarchical Clustering of Key Attributes

  25. Circular Heatmap Example • http://prcweb.co.uk/circularheatchart/

  26. Scatterplot Matrix (SPLOM) D3.js SPLOM example: http://mbostock.github.io/d3/talk/20111116/iris-splom.html

  27. Parallel Coordinates

  28. SPLOM vs. Parallel Coordinates

  29. Correlation with Parallel Coordinates

  30. Parallel Coordinates Examples • With brush filtering and reorderable axes • http://bl.ocks.org/jasondavies/1341281 • With k-means clustering (from Wikipedia):

  31. Preparation for Next Class • Read Munzner Chapter 7 • Scott Murray’s D3 Tutorial • http://alignedleft.com/tutorials/d3/ • Bring in interesting high-dimensional tabular datasets (can use for Lab 3)

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