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Dataviz: back to basics
A look at what makes a dataviz work
Cédric Lombion
- Open Data portal
- Semi-structured data (website)
- Private data (partnership)
- PDF : Tabula
- Website : scraping/API
- Graphs : GraphClick
- Will this data answer our initial
question?
- Is the data of sufficient quality?
- Fuse (Vlookup, csvkit…)
- Formatting cleaning (OpenRefine)
- Content cleaning
- Simple analysis (spreadsheet)
- advanced analysis (R, Python)
- Physical visualisations
- Interactive visualisations
- Static visualisations
- Web applications
datavisualization infographics
datavisualization infographics
explanatory exploratory
datavisualization infographics
explanatory
exploratory
informative persuasive artistic
datavisualization infographics
explanatory
exploratory
informative persuasive
artistic
+
Let’s play!
Variables/data dimensions
= +3
= -2
Cédric Lombion
cedric.lombion@okfn.org
schoolofdata.org
datavizcatalogue.com
Dataviz presentation at ThingsKamp2015 Istanbul
Dataviz presentation at ThingsKamp2015 Istanbul
Dataviz presentation at ThingsKamp2015 Istanbul
Dataviz presentation at ThingsKamp2015 Istanbul
Dataviz presentation at ThingsKamp2015 Istanbul
Dataviz presentation at ThingsKamp2015 Istanbul
Dataviz presentation at ThingsKamp2015 Istanbul
Dataviz presentation at ThingsKamp2015 Istanbul
Dataviz presentation at ThingsKamp2015 Istanbul
Dataviz presentation at ThingsKamp2015 Istanbul
Dataviz presentation at ThingsKamp2015 Istanbul
Dataviz presentation at ThingsKamp2015 Istanbul
Dataviz presentation at ThingsKamp2015 Istanbul
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Dataviz presentation at ThingsKamp2015 Istanbul

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Dataviz presentation at ThingsKamp2015 Istanbul. Intended for newcomers to information visualisation, with the test of the first prototype of a dataviz card game.

Publié dans : Données & analyses
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Dataviz presentation at ThingsKamp2015 Istanbul

  1. 1. Dataviz: back to basics A look at what makes a dataviz work
  2. 2. Cédric Lombion
  3. 3. - Open Data portal - Semi-structured data (website) - Private data (partnership)
  4. 4. - PDF : Tabula - Website : scraping/API - Graphs : GraphClick
  5. 5. - Will this data answer our initial question? - Is the data of sufficient quality?
  6. 6. - Fuse (Vlookup, csvkit…) - Formatting cleaning (OpenRefine) - Content cleaning
  7. 7. - Simple analysis (spreadsheet) - advanced analysis (R, Python)
  8. 8. - Physical visualisations - Interactive visualisations - Static visualisations - Web applications
  9. 9. datavisualization infographics
  10. 10. datavisualization infographics explanatory exploratory
  11. 11. datavisualization infographics explanatory exploratory informative persuasive artistic
  12. 12. datavisualization infographics explanatory exploratory informative persuasive artistic
  13. 13. +
  14. 14. Let’s play!
  15. 15. Variables/data dimensions
  16. 16. = +3 = -2
  17. 17. Cédric Lombion cedric.lombion@okfn.org schoolofdata.org datavizcatalogue.com

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