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© J.F. Campbell UM St. Louis Data Visualization
© J.F. Campbell UM St. Louis Overview 1.Why use visualization? 2.Types of visualizations. 3.Design guidelines. 4.Infographics. 5.Tableau example. Visualize This Much of this is drawn from materials at the Duke University Library Data Visualization site:
© J.F. Campbell UM St. Louis Why not Statistics? Consider the following four sets of 11 (x,y) coordinates: Are they similar? xy xy xy xy
© J.F. Campbell UM St. Louis Summary Statistics Statistically, they seem pretty similar… Mean: Variance: Correlation: Linear regression line = X for all 4! xy xy xy xy
© J.F. Campbell UM St. Louis Similar? xy xy
© J.F. Campbell UM St. Louis Why Visualization? To discover new things about your data. –The most effective way for humans to understand complex data (and large amounts of data) is visually! To tell a story using data. To provoke and answer questions. To facilitate analysis. To better communicate. Visualization leverages human visual capabilities for data analysis.
© J.F. Campbell UM St. Louis The Great One
© J.F. Campbell UM St. Louis Stages 1.Identify the topic of interest and relevant questions. 2.Obtain useful and relevant data. 3.Explore the data to identify interesting relationships: Look for trends, patterns and differences across categories, space and time. 4.Represent the data (maps, charts, etc.). 5.Refine the presentation with your audience in mind. 6.Provide tools to manipulate or interact with the data.
© J.F. Campbell UM St. Louis Types of Visualizations 1.2D and Planar (geospatial): a.Types: Choropleth, Cartogram… b.Use a map to show where something is. c.Maps are best combined with other charts to provide details on what the map shows. 2.Temporal: For changes over time. a.Time series or line chart. b.Stream graph. c.Polar chart.
© J.F. Campbell UM St. Louis Temporal Charts
© J.F. Campbell UM St. Louis Sankey diagram: Map flows. 2.Histogram or bar chart. Types of Visualizations
© J.F. Campbell UM St. Louis Bubble chart. With motion : Types of Visualizations
© J.F. Campbell UM St. Louis Types of Visualizations 4.Tree maps and hierarchical charts.
© J.F. Campbell UM St. Louis Types of Visualizations 5.Networks. Vaccine game: 6.Radar chart.
© J.F. Campbell UM St. Louis Baseball Visualizations Spray charts for Justin Heyward Wainwright’s 1 st pitch to RH batter: strike=67.4% batter Pitch to RH batter with 0-2 count: strike=46.0% batter
© J.F. Campbell UM St. Louis Visualizing Wind Live:
© J.F. Campbell UM St. Louis Design Design is not just what it looks like and feels like. Design is how it works. –Steve Jobs, 2003 Clarity Aesthetics Confusing Ugly Beautiful Clear Yes No ? ?
© J.F. Campbell UM St. Louis Design From Confusing Ugly Beautiful Clear
© J.F. Campbell UM St. Louis Design From
© J.F. Campbell UM St. Louis Visualization Design Guidelines The visualization must have a purpose! –All elements should work together to achieve the purpose. –What questions can or does it answer? –What questions should it answer? Be simple and succinct. –Show the main points – do not make the audience try to figure it out. –Do not present too much information! (Limit a dashboard to 2-4 elements/views). Any interactivity should be obvious to the viewer.
© J.F. Campbell UM St. Louis Visualization Design Guidelines Many visualizations combine several elements (views, charts, etc.) in a “dashboard”. Place the most important view at the top, or top left. Be sure the legends are associated with the correct view. –Position legends to the right of the view, if possible. If elements are linked interactively, arrange them top to bottom and left to right, with the linking and filtering starting at the top.
© J.F. Campbell UM St. Louis Choosing a Good Chart
© J.F. Campbell UM St. Louis Design Guidelines: Charts Put the most important data on the rows and columns (x and y axes); Use color and size for less important attributes. Bar charts are usually better than pie charts: –Areas in pie charts are difficult to estimate, and the eye can compare only adjacent slices. –Put labels on the bars. Do not use 3D charts. Make sure all axes are understandable. –Axis scales must be consistent. With line charts, limit the number if lines and highlight the most important line(s).
© J.F. Campbell UM St. Louis Line Charts #1 Keep it simple! Label the lines, instead of using a legend.
© J.F. Campbell UM St. Louis Highlight what is important. Line Charts #2 Is the baseline 0?
© J.F. Campbell UM St. Louis Elevate the axis if baseline is not 0 Line Charts #3 Use a good aspect ratio.
© J.F. Campbell UM St. Louis Bar Charts Use horizontal bar charts, rather than vertical bar charts.
© J.F. Campbell UM St. Louis Tables? From
© J.F. Campbell UM St. Louis Color Color is important! Choose colors intelligently. –Use at most 6 colors. –Use no more than two color palettes. –Use meaningful colors (pink/blue; red/green, etc.), but be aware that colors are culturally dependent Avoid multiple schemes. Some colors do not work well together!!
© J.F. Campbell UM St. Louis Color Vary the saturation level (lightness), not the hue (color). Consider that your visualization may be printed in black and white.
© J.F. Campbell UM St. Louis Color Can Be Deceiving… Which square is darker – A or B? Which is darker – A, B or C?
© J.F. Campbell UM St. Louis More Colors Which dog is bluer? How many colors are in this?
© J.F. Campbell UM St. Louis Points What do you see here? Most points are blue, one is red and four are green. The points are spread out “evenly” over the space. What do you see here? Differences are more difficult to distinguish with symbols alone.
© J.F. Campbell UM St. Louis Points Again… You may not appreciate that one point is very unusual point - both an uncommon color and an uncommon shape (the green square) Combining color and shape does not work well! What do you see here? Most points are blue, one is red and some are green. Some are squares, but most are dots; one is a +. The points are spread out “evenly” over the space.
© J.F. Campbell UM St. Louis Fonts Use only a few fonts: –Verdana or Trebuchet for numbers. –Arial, Georgia, Tahoma, Times New Roman, Lucida Sans. Use a few appropriate font sizes. Change adjacent fonts by only one attribute (bold or underline, not both): –A good change A Bad change
© J.F. Campbell UM St. Louis Infographics A common type of visualization specific to a particular context. Usually created for a single dataset for a particular purpose. Not designed for the user to explore the data. Most view infographics as a type of visualization; but some see it the opposite way.
© J.F. Campbell UM St. Louis Infographic 1
© J.F. Campbell UM St. Louis Infographic 2
© J.F. Campbell UM St. Louis Infographic 3
© J.F. Campbell UM St. Louis Summary Use the real estate wisely. Show the main points – do not make the audience try to figure it out. Do not present too much information! Do the squint test: –What stands out? What do you see? Show it to someone else and ask what they see. Include the source of the data.
© J.F. Campbell UM St. Louis A great site for visualization basics. A great site for Tableau information. More design guidance… Basic Information
© J.F. Campbell UM St. Louis Baby Names in Tableau Consider the top baby name in each US state for each year… What to call on 4 th down?
© J.F. Campbell UM St. Louis Data for Baby Names in Tableau Original Data: Every baby name used >5 times, by state and by year since State, Gender, Year, Name, # of occurrences From this, extract the top male and female name for each state for each year. AK,F,1910,Mary,14 AK,F,1910,Annie,12 AK,F,1910,Anna,10 AK,F,1910,Margaret,8 AK,F,1910,Helen,7 AK,F,1910,Elsie,6 AK,F,1910,Lucy,6 AK,F,1910,Dorothy,5 AK,F,1911,Mary,12 AK,F,1911,Margaret,7 AK,F,1911,Ruth,7 AK,F,1911,Annie,6 AK,F,1911,Elizabeth,6 AK,F,1911,Helen,6 AK,F,1912,Mary,9 AK,F,1912,Elsie,8 AK,F,1912,Agnes,7 AK,F,1912,Anna,7 AK,F,1912,Helen,7 AK,F,1912,Louise,7 AK,F,1912,Jean,6 AK,F,1912,Ruth,6 AK,F,1912,Alice,5 AK,F,1912,Esther,5
© J.F. Campbell UM St. Louis Tableau Dashboard Number of different top male (blue) and female (pink) names in the 50 states since 1910 Top name in each state for chosen year Frequency of name (for top names) Trend of name as the top name in states over time YEAR Gender
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