Data Visualization Session 4: Designing Data Visuals
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Data visualization Session 4: Designing data visuals Koen Van den Eeckhout - Baryon All the slides and all the links: baryon.be/dataviz-resources Session 1 Design basics Tuesday, September 21, 2 pm – 5.15 pm Session 2 Graphic representation Wednesday, September 22, 9 am – 12.15 pm homework assignment part 1 Session 3 Producing data visuals Tuesday, October 5, 2 pm – 5.15 pm Session 4 Designing data visuals Wednesday, October 6, 9 am – 12.15 pm homework assignment part 2 Session 5 Feedback Tuesday, October 19, 2 pm – 3.30 pm Components Colors Illustrations Typography 15’ break Advanced Interactive data visuals data visualization Programming data visuals Maps Components trust, happiness, stability warmth energy, sensitive, passion love friendly, rich, natural mistery history, neutral, intelligence calm canva.com canva.com coolors.co Accent colors Accent colors Clever color use Accessibility Accessibility https://academy.datawrapper.de/article/140-what-to-consider- when-choosing-colors-for-data-visualization are colors even helpful? gray is the most powerful color use consistent colors use logical colors https://blog.datawrapper.de/gendercolor/ https://blog.datawrapper.de/gendercolor/ dark colors = high values* *on a light background don’t use gradient colors for categories rainbow scales can be confusing Icons thenounproject.com * The most important use cases for 5G Illustrations freepik.com Typography Typography Typography Typography Typography Typography Serif Sans serif perfect for body text perfect for titles fonts.google.com Some personal favorites Open sans Bahnschrift Lato Roboto Captions Well-crafted captions can make a visual ‘self-contained’ data story makeovermonday.co.uk Font size Adapt to the situation – a presentation is different from an article! How would you do it? Individual exercise (10 minutes) Write down what you don’t like about this visual What would you change to improve it? Break All the slides and all the links: https://baryon.be/dataviz-resources Advanced data visualization Interactivity Types of interactivity tooltips filtering navigation storytelling Types of interactivity tooltips filtering navigation storytelling https://baryon.be/files/MM/2020/W04/ Types of interactivity tooltips filtering navigation storytelling Noah Veltman https://noahveltman.com/nflplayers/ Types of interactivity tooltips filtering navigation storytelling Jeff Clark http://neoformix.com/Projects/ObesitySlope/ Types of interactivity tooltips filtering navigation storytelling De Tijd https://multimedia.tijd.be/biotechrevolutie/ Interactivity Datawrapper LocalFocus Flourish datawrapper.de localfocus.nl flourish.studio https://baryon.be/files/MM/2020/W04/ https://baryon.be/data-visualization-tools-datawrapper/ Demo Programming Programming languages for data visualization R python JavaScript R ggplot2 https://r4ds.had.co.nz/data- visualisation.html https://www.cedricscherer.com/ 2019/08/05/a-ggplot2-tutorial- for-beautiful-plotting-in-r/ Python Matplotlib https://matplotlib.org/ Seaborn http://web.stanford.edu/~mwask om/software/seaborn/index.html Plotly https://plot.ly/python/ JavaScript d3.js https://d3js.org/ Highcharts https://www.highcharts.com/ docs/index Chart.js https://www.chartjs.org/ Choosing a library supported chart types features interactivity ease of use community support Maps (Some) mapping tools Mapbox QGIS Datawrapper Google Earth and more? (Some) mapping tools Mapbox QGIS Datawrapper Google Earth and more? Mapbox https://studio.mapbox.com (Some) mapping tools Mapbox QGIS Datawrapper Google Earth and more? (Some) mapping tools Mapbox QGIS Datawrapper Google Earth and more? Pen & paper QGIS & Aerialod http://www.statsmapsnpix.com/2020/11/ how-to-make-3d-population-density.html Azimuthal map tool & Adobe Illustrator https://ns6t.net/azimuth/ ??? Excel & Adobe Illustrator https://baryon.be/ behind-the-maps/ Homework assignment Bringing it all together Homework assignment Revisit the concept(s) you sketched in the first part of the assignment Feel free to take feedback into account, modify the concept where needed. Choose a tool you like to turn this concept into a data visual Think carefully about the use of colors, typography, icons,… A data visual is never finished… limit yourself to about 2, but maximum 4 hours Submit the visual as an image file or link before Monday, October 18: • to [email protected] • or through Moodle Session 1 Design basics Tuesday, September 21, 2 pm – 5.15 pm Session 2 Graphic representation Wednesday, September 22, 9 am – 12.15 pm homework assignment part 1 Session 3 Producing data visuals Tuesday, October 5, 2 pm – 5.15 pm Session 4 Designing data visuals Wednesday, October 6, 9 am – 12.15 pm homework assignment part 2 Session 5 Feedback Tuesday, October 19, 2 pm – 3.30 pm Q&A All the slides and all the links: https://baryon.be/dataviz-resources Koen Van den Eeckhout – [email protected] - @koen_vde.