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Datascapes 2018 data visualisation

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During this last Saturday I had the opportunity to discover the word of data analysis and visualisation.

Data visualisation

Font

Font-type: sans-serif serif
Font size
Fype face / weight: light italics bold
Emphasis: font Font Font

Fewer font types and faces are better
Choose font accordingly

Color

Color contrast
Color theory (use websites that can help with colors)
Fewer colors, use selection helpers
http://w3chools.com/colors (Color schemes)
colorbrewer2.org

Symbologie
Graphical semiotics by Bertin 1974

Charts
Bars
Histograms
Heatmaps
Density functions
If it doesn’t add any value than don’t do it (2d vs 3d excel charts)

Classifications
Quantiles classification (hardest)

User helpers in your charts (User better legend)

Programming tools

R language and R studio are powerful tools to quickly display data into charts and filter data to display big data sets

ggplot2 in R

D3.js

Story maps (visualizing the context)

Here are the data sets that we where using the Hackathon most of them are from the city of Montreal open data website GitHub: https://github.com/CSCDS/datascapes-2017

http://donnees.ville.montreal.qc.ca/

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