====== Visualización ======
* {{https://pbs.twimg.com/media/Cy7iwj_VIAAijAs.jpg?800}}
* We investigated how data-driven stories work, how they are different from other types of narratives and also other types of data visualization. -> http://napa-cards.net/#info
* https://www.r-bloggers.com/7-visualizations-you-should-learn-in-r/
((https://i1.wp.com/www.tatvic.com/blog/wp-content/uploads/2016/12/Pic_2.png)){{https://i1.wp.com/www.tatvic.com/blog/wp-content/uploads/2016/12/Pic_2.png?800}}
* http://infowetrust.com/history/
{{:personas:brolin:data_analisis:pasted:20170110-143733.png?800}}
* Data Humanism
https://medium.com/@giorgialupi/data-humanism-the-revolution-will-be-visualized-31486a30dbfb#.huv43zpei
* Visualización de información
Según Tufte http://www.edwardtufte.com/tufte:
Los gráficos toman un grupo de números para ilustrar tendencias y eventos inusuales. Permiten identificar patrones. Para grupos de números muy grandes la única forma de ver a información es a partir de gráficos.
Los gráficos tienen la intención de describir, comparar o decorar
Algunos elementos
Chartjunk: Decoración en el gráfico que distrae
Small multiples: Muchas vistas de los datos que permiten comparar
Micro and Macro: Mostrar datos en múltiples escalas
Graphical Excellence: Presentación de ideas complejas comunicadas con claridad, precisión y eficiencia
Graphic integrity: Se debe considerar el efecto de lo que se dice con el gráfico y buscar eliminar todas las falsas impresiones
Visual impression: Cuidar que sea correcta. Se recomienda ilustrar un conjunto de medida a la vez. Más de dos puede generar confusión
Del libro Envisioning information:
Escaping flatland
Micro/macro readings
Layering and separation
Small multiples
Color and information
Narratives of space and time
Visualización de grandes tablas
http://www.bytemuse.com/post/data-comb-visualization/ https://www.youtube.com/watch?v=s1ueC7WvKAo https://www.cs.ubc.ca/~tmm/courses/cpsc533c-04-fall/readings/tablelens.pdf
Uso de R en NYT para la creación de visualizaciones
http://datastori.es/ds-56-amanda-cox-nyt/
A collection of open access visualization research at the VIS 2017 conference. Info about the symbols and open access. To edit the data, see GitHub. -> http://oavis.steveharoz.com/\\
Data Visualization for Social Science -> http://socviz.co\\
**Libros de R**\\
http://r4ds.had.co.nz/tidy-data.html\\
https://adv-r.hadley.nz/\\
**Dashboard design**
https://www.displayr.com/8-types-of-online-dashboards/?utm_medium=Feed&utm_source=Syndication
===== Referentes =====
https://distill.pub/2016/misread-tsne/?utm_content=buffera4d62&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer\\
**AMA's**
''Calendario'' -> https://calendar.google.com/calendar/embed?src=dataisbeautifulama@gmail.com&ctz=America/New_York\\
https://www.reddit.com/r/dataisbeautiful/comments/75q0qi/im_shirley_wu_freelance_data_visualization/\\
https://www.reddit.com/r/dataisbeautiful/comments/72c06m/im_elijah_meeks_author_of_d3js_in_action_and/\\
https://www.reddit.com/r/dataisbeautiful/comments/3k3if4/hi_im_mike_bostock_creator_of_d3js_and_a_former/\\
**Multivariate Maps**
http://vallandingham.me/multivariate_maps.html
**Libro ** http://socviz.co/lookatdata.html
{{:personas:brolin:data_analisis:2018-07-15-195652_1154x758_scrot.png | }}is a classification of chart types based on input data format. It comes in the form of a decision tree leading to a set of potentially appropriate visualizations to represent the dataset. -> https://www.data-to-viz.com/#connection
Chart Maker -> http://chartmaker.visualisingdata.com/
Map Pins
{{:personas:brolin:data_analisis:2019-08-31-201911_673x511_scrot.png|}}
https://99percentinvisible.org/article/cartopinography-the-unlikely-study-of-map-pins-flags-beads-other-markers/
**Top 50 ggplot2 Visualizations - The Master List (With Full R Code)**
http://r-statistics.co/Top50-Ggplot2-Visualizations-MasterList-R-Code.html
===== Referentes =====
* https://www.nytimes.com/interactive/2020/08/24/climate/racism-redlining-cities-global-warming.html