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5 yıl önce
5 yıl önce
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  1. # Dataviz ressources
  2. ## books
  3. [Interactive Data Visualization for the Web](http://shop.oreilly.com/product/0636920037316.do) , Scott Murray, O’Reilly (2017)
  4. [Visualization Analysis and Design](http://www.amazon.com/Visualization-Analysis-Design-Peters-Series/dp/1466508914) , Tamara Munzner, CRC Press (2014)
  5. [The Functional Art: An introduction to information graphics and visualization](http://www.amazon.com/The-Functional-Art-introduction-visualization/dp/0321834739/) , Alberto Cairo, New Riders (2012)
  6. [Visual Thinking for Design](http://www.amazon.com/Visual-Thinking-Kaufmann-Interactive-Technologies/dp/0123708966) , Colin Ware, Morgan Kaufman (2008)
  7. [Data Visualization](https://socviz.co)
  8. [Fundamentals of Data Visualization](https://serialmentor.com/dataviz/)
  9. ## Cours
  10. https://lyondataviz.github.io/teaching/lyon1-m2/2016/pdfs/1_introduction.pdf
  11. [DataViz Cours Lyon1 M2 2018-2019](https://lyondataviz.github.io/teaching/lyon1-m2/2018/)
  12. [Resources: InfoVis @ UBC CS](http://www.cs.ubc.ca/group/infovis/resources.shtml)
  13. [Les données spatiales avec R](https://maeltheuliere.github.io/rspatial/creer-des-cartogrammes.html)
  14. [https://vallandingham.me/textvis-talk/#4]()
  15. ## Web
  16. [WTF Visualizations](https://viz.wtf)
  17. [deck.gl](https://deck.gl/#/)
  18. [tuning ggplot themes](https://evamaerey.github.io/little_flipbooks_library/taming_themes_in_ggplot/taming_ggplot_themes.html#1)
  19. https://data.world
  20. [The Evolution of a ggplot (Ep. 1)-Cédric Scherer](https://cedricscherer.netlify.com/2019/05/17/the-evolution-of-a-ggplot-ep.-1/)
  21. ## Talks
  22. ### Dataveyes
  23. [CAROLINE GOULARD & LUDOVIC RIFFAULT - OpenVis Conf 2018 - YouTube](https://www.youtube.com/watch?v=9aVUtluzvNE&feature=youtu.be)
  24. https://www.linkedin.com/in/carolinegoulard/
  25. ## Packages
  26. ggpubr: publication ready plots
  27. [‘ggplot2’ Based Publication Ready Plots • ggpubr](https://rpkgs.datanovia.com/ggpubr/)
  28. ## Programme
  29. ### Lundi
  30. * Cours 1
  31. * Introduction visualisation : Quoi ? Pourquoi ? Qui ? Comment ?
  32. * Types de datasets, types de données, sémantique, table data/autres
  33. * Lab 1
  34. * RStudio
  35. * ggplot2, grammar of graphics
  36. ### Mardi
  37. #### Matin
  38. * Cours 2
  39. * Perception: système visuel, marques et canaux, couleurs
  40. * Abstraction de tache
  41. * Lab 2
  42. * tidy data, wrangling
  43. * ggplot2
  44. #### Après-midi
  45. * Cours 3
  46. * Principes de design
  47. * Visualisation de données tabulaires
  48. * Lab 3
  49. * Presentation du projet
  50. * Web scraping
  51. * Recherche de dataset
  52. ### Mercredi
  53. #### Matin
  54. * Cours 4
  55. * Visualisation de données tabulaires
  56. * Interaction
  57. * Lab 4
  58. * tidy data
  59. #### Après-midi
  60. * Cours 5
  61. * Visualisation de données spatiales
  62. * Lab 5
  63. * maps, leaflet
  64. ### Jeudi
  65. #### Matin
  66. * Cours 6
  67. * Visualisation de graphs
  68. * Lab 6
  69. * networks
  70. #### Après-midi
  71. * Cours 7
  72. * Visualisation de texte
  73. * Lab 7
  74. * tidy text, word embeddings, …
  75. ### Vendredi
  76. #### Matin
  77. * Cours 8
  78. * Visualisation de données temporelles
  79. * Lab 8
  80. * séries temporelles
  81. #### Après-midi
  82. * Lab 9
  83. * projet