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Learn to identify and visualize trends in time-series data using various charts like bar graphs, scatter plots, line charts, and more for effective data analysis and interpretation. Course materials include practical examples and techniques.
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Visualisation2012 - 2013Lecture 3 Visualising Trends Brian Mac Namee Dublin institute of Technology Applied Intelligence Research Centre
Origins • This course is based heavily on a course developed by Colman McMahon (www.colmanmcmahon.com) • Material from multiple other online and published sources is also used and when this is the case full citations will be given
Visualization of the Week www.pinterest.com/brianmacnamee/great-visualisation-examples/
(Un)Visualization of the Week www.pinterest.com/brianmacnamee/terrible-visualisation-examples/
Agenda • Visualising patterns over time • Discrete points in time • Continuous points in time • Handling multiple dimensions over time
What To Look For • The most common thing you look for in time series, or temporal, data is trends • Is something increasing or decreasing? • Are there seasonal cycles? • To find these patterns, you have to look beyond individual data points to get the whole picture
Visualising Patterns Over Time • Visualising patterns over time • Discrete points in time • Bar Graph • Scatter Plot • Continuous points in time • Line Chart • Step Chart • Handling multiple dimensions over time • Stacked Bar Chart • Area Chart • Stream Graph • Small Multiples • Animation
Discrete Points In Time • Often we have datasets that contain single measurements for a reasonably small number of discrete points in time • Profit per year • Rainfall per month • In these cases a simple bar graph is often appropriate
Simple Bar Graph “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do
Simple Bar Graph “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do
Simple Bar Graph http://www.mornpen.vic.gov.au/page/imageThumbnail.asp?C_Id=820
Continuous Points In Time • Often we have datasets that contain single measurements for a number of continuous points of time • Stock prices over time • Internet traffic over time • In these cases a line charts are more appropriate
Simple Scatter Plot “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do
Simple Scatter Plot “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do
Simple Line Chart • Simply adding a line to a scatter plot can help greater emphasise a trend over time “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do
Simple Line Chart “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do
Simple Line Chart “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do
Step Chart • Basic line charts interpolate the change in measurement from one point in time to another • Often this is not appropriate and in these cases step charts are more appropriate “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do
Step Chart “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do
Step Chart “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do
Fitting A Line • In some cases adding a line to a scatter plot can mask the trend over time rather than help illustrate it • In this cases it can be more appropriate to fit a line or curve to a dataset so as to highlight a trend in time • ACHTUNG: Be careful when fitting lines, it is possible to illustrate trends that don’t really exist
Fitting A Line “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do
Smoothing & Estimation “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do
Multiple Dimensions In Time • Often we have datasets that contain multiple measurement for each point in time which gives us multiple dimensions • This makes visualization more challenging as we need to use newer and different encodings • There are a number of approaches we can take
Stacked Bar Chart “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do
Stacked Bar Chart Charting U.S. Gun Manufacturing, Matt Stiles, The Daily Viz, 2012 http://thedailyviz.com/2012/08/07/charting-u-s-gun-manufacturing/
Stacked Bar Chart • Interpreting multiple time series in a stacked bar chart can be really difficult, especially when we need to interpret the trend within the higher categories • Only really appropriate when the real trend we want to illustrate is the overall total bar height trend and the individual categories are secondary
Multiple Line Series http://hci.stanford.edu/jheer/files/zoo/ex/time/index-chart.html
Multiple Line Series U.S. Gun Manufacturing By Type Displaying time-series data: Stacked bars, area charts or lines…you decide!, VizWiz, 2012 http://vizwiz.blogspot.ie/2012/08/displaying-time-series-data-stacked.html
Stacked Area Chart “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do
Stacked Area Chart U.S. Gun Manufacturing By Type Displaying time-series data: Stacked bars, area charts or lines…you decide!, VizWiz, 2012 http://vizwiz.blogspot.ie/2012/08/displaying-time-series-data-stacked.html
Stacked Area Chart • Stacked area charts unfortunately suffer from many of the same problems as stacked bar charts • It can be very hard to interpret the trends of each category as they are stacked on top of each other
Stacked Area Chart What does the shotgun trend look like? Displaying time-series data: Stacked bars, area charts or lines…you decide!, VizWiz, 2012 http://vizwiz.blogspot.ie/2012/08/displaying-time-series-data-stacked.html
Stacked Area Chart Displaying time-series data: Stacked bars, area charts or lines…you decide!, VizWiz, 2012 http://vizwiz.blogspot.ie/2012/08/displaying-time-series-data-stacked.html
Stream Graph • The Stream Graph is an attempt to overcome the difficulties associated with stacked bar charts and stacked area charts
Stream Graph ThemeRiver: Visualizing Theme Changes over Time, Susan Havre , Beth Hetzler , Lucy Nowell, Proc. IEEE Symposium on Information Visualization, 2000.http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.135.4974
Stream Graph ThemeRiver: Visualizing Theme Changes over Time, Susan Havre , Beth Hetzler , Lucy Nowell, Proc. IEEE Symposium on Information Visualization, 2000.http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.135.4974
Stream Graph Stacked Graphs – Geometry & Aesthetics, Lee Byron & Martin Wattenberg, 2008.http://www.leebyron.com/what/lastfm/
Stream Graph Stacked Graphs – Geometry & Aesthetics, Lee Byron & Martin Wattenberg, 2008.http://www.leebyron.com/what/lastfm/
Stream Graph Stacked Graphs – Geometry & Aesthetics, Lee Byron & Martin Wattenberg, 2008.http://www.leebyron.com/what/lastfm/
Stream Graph http://hci.stanford.edu/jheer/files/zoo/ex/time/stack.html
Stream Graph The Ebb and Flow of Movies: Box Office Receipts 1986 — 2008, New York Timeshttp://www.nytimes.com/interactive/2008/02/23/movies/20080223_REVENUE_GRAPHIC.html
Small Multiples • One solution to illustrating time is to use small multiples to show multiple snapshots of the data at different points in time
Small Multiples http://hci.stanford.edu/jheer/files/zoo/ex/time/multiples.html
Small Multiples TresEpistolae de MaculisSolaribusScriptae ad Marcum Welserum, ChristophScheiner, 1612 http://galileo.rice.edu/sci/observations/sunspots.html
Animation • Animation is obviously a great way to illustrate changes over time • We will look at this more later in the course
Animation www.ted.com/talks/hans_rosling_shows_the_best_stats_you_ve_ever_seen.html
Animation Gallileo made flip books of sunspot images to show how they moved over time Galileo's Sunspot Drawingshttp://galileo.rice.edu/sci/observations/ssm_slow.mpg