class: center, middle, inverse, title-slide # <code style='background:none;font-size:1.1em'>library(<strong>highcharter</strong>)</code><br>¡De principiante a experto! ## Latin<strong>R</strong><br>Santiago, CL - Septiembre 2019 ### Joshua Kunst & Ignacio Rossi --- class: clear, right, bottom background-image: url("img/trip.jpg") background-size: cover # Antes de Partir --- # Como seguir el taller - Descargar el proyecto R-Studio https://bit.ly/2kGGltk (comprimido) - Descomprimir, yay! - Abrir el proyecto: doble click en el archivo `LatinR-2019-Highcharter-taller.Rproj` - Códigos y ejercicios en carpeta `R` - Slides en la ruta `slides/index.html` o versión online de las slides en http://jkunst.com/LatinR-2019-Highcharter-taller/slides/ - En las slides lo que aparezca de `esta forma` indica que es código (generalmente) - Internet: 1) eduroam 2) red UC_CentroExtension Password plaza.2020 --- # Evitar errores usuales - Siempre correr los scripts en orden: línea por línea - ¡Sí! Comenzando por la primera - En caso de <code style="color:red">Warning: ... </code>, es un warning no más, nada grave. - En caso de <code style="color:red">Error ... </code>, leerlo con calma y en caso de no poder solucionarlo levantar la manto para ser socorrido - En caso de <code style="color:red">Error ... </code>, leerlo con calma y en caso de no poder solucionarlo levantar la manto para ser socorrido - En caso de <code style="color:red">Error ... </code>, leerlo con calma y en caso de no poder solucionarlo levantar la manto para ser socorrido --- # Los paquetes Necesitaremos de tidyverse: `dplyr` y `purrr` en algunos casos para manipulación de datos y datos. ```r if(!require(tidyverse)) install.packages("tidyverse") if(!require(datos)) install.packages("datos") if(!require(gapminder)) install.packages("gapminder") if(!require(tradestatistics)) install.packages("tradestatistics") if(!require(highcharter)) install.packages("highcharter") library(tidyverse) library(datos) library(tradestatistics) # y lo más importante supongo :P library(highcharter) ``` --- # Prueba de fuego ```r highcharts_demo() ``` <div id="htmlwidget-2a44d95725fdaaac95e3" style="width:100%;height:500px;" class="highchart html-widget"></div> <script type="application/json" data-for="htmlwidget-2a44d95725fdaaac95e3">{"x":{"hc_opts":{"title":{"text":"Monthly Average Temperature"},"yAxis":{"title":{"text":"Temperature"}},"credits":{"enabled":false},"exporting":{"enabled":false},"plotOptions":{"series":{"label":{"enabled":false},"turboThreshold":0},"treemap":{"layoutAlgorithm":"squarified"}},"subtitle":{"text":"Source: WorldClimate.com"},"xAxis":{"title":{"text":"Months"},"categories":["Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"]},"series":[{"data":[7,6.9,9.5,14.5,18.2,21.5,25.2,26.5,23.3,18.3,13.9,9.6],"name":"Tokyo"},{"data":[3.9,4.2,5.7,8.5,11.9,15.2,17,16.6,14.2,10.3,6.6,4.8],"name":"London"},{"data":[-0.9,0.6,3.5,8.4,13.5,17,18.6,17.9,14.3,9,3.9,1],"name":"Berlin"}]},"theme":{"chart":{"backgroundColor":"transparent"}},"conf_opts":{"global":{"Date":null,"VMLRadialGradientURL":"http =//code.highcharts.com/list(version)/gfx/vml-radial-gradient.png","canvasToolsURL":"http =//code.highcharts.com/list(version)/modules/canvas-tools.js","getTimezoneOffset":null,"timezoneOffset":0,"useUTC":true},"lang":{"contextButtonTitle":"Chart context menu","decimalPoint":".","downloadJPEG":"Download JPEG image","downloadPDF":"Download PDF document","downloadPNG":"Download PNG image","downloadSVG":"Download SVG vector image","drillUpText":"Back to {series.name}","invalidDate":null,"loading":"Loading...","months":["January","February","March","April","May","June","July","August","September","October","November","December"],"noData":"No data to display","numericSymbols":["k","M","G","T","P","E"],"printChart":"Print chart","resetZoom":"Reset zoom","resetZoomTitle":"Reset zoom level 1:1","shortMonths":["Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"],"thousandsSep":" ","weekdays":["Sunday","Monday","Tuesday","Wednesday","Thursday","Friday","Saturday"]}},"type":"chart","fonts":[],"debug":false},"evals":[],"jsHooks":[]}</script> --- class: clear, middle, left background-image: url("img/strc.jpg") background-size: cover # Estructura<br>taller --- # Temas - ¿Por que la visualización? 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Yo procederé a cambiar el tema por default de highcharts que no me gusta mucho: ```r options(highcharter.theme = hc_theme_smpl()) ``` Usted puede buscar su favorito, por ejemplo: ```r options(highcharter.theme = hc_theme_ggplot2()) ``` Más variedad en http://jkunst.com/highcharts-themes-collection/ --- # Datos a probar ```r diamantes ``` ``` ## # A tibble: 53,940 x 10 ## precio quilate corte color claridad profundidad tabla x y z ## <int> <dbl> <ord> <ord> <ord> <dbl> <dbl> <dbl> <dbl> <dbl> ## 1 326 0.23 Ideal E SI2 61.5 55 3.95 3.98 2.43 ## 2 326 0.21 Premi~ E SI1 59.8 61 3.89 3.84 2.31 ## 3 327 0.23 Bueno E VS1 56.9 65 4.05 4.07 2.31 ## 4 334 0.290 Premi~ I VS2 62.4 58 4.2 4.23 2.63 ## 5 335 0.31 Bueno J SI2 63.3 58 4.34 4.35 2.75 ## 6 336 0.24 Muy b~ J VVS2 62.8 57 3.94 3.96 2.48 ## 7 336 0.24 Muy b~ I VVS1 62.3 57 3.95 3.98 2.47 ## 8 337 0.26 Muy b~ H SI1 61.9 55 4.07 4.11 2.53 ## 9 337 0.22 Regul~ E VS2 65.1 61 3.87 3.78 2.49 ## 10 338 0.23 Muy b~ H VS1 59.4 61 4 4.05 2.39 ## # 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Revisemos el archivo `R/01-hchart.R` ] --- # hchart en data frames El caso de data frame es particular: - En una data frame (tabla) pueden existir varias columnas las cuales querríamos representar o no visualmente en un gráfico - Debemos _hacer el esfuerzo_ de mencionar comos queremos _mapear_ (¡¿KHÉ?!) las variables; y que variables - Y obviamente mencionar el tipo de representación -tipo de gráfico- a usar. - En data frames `hchart` funciona relativamente parecido a `ggplot2` --- # ¿Qué es esto de _mapear_? 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htmlwidget, por lo que es _shiny-ready_ - Y con la flexibilidad de `shiny` y `highcharter` puedes hacer lo que te de la gana - Ejemplos: https://centre.humdata.org/fighting-rumors-to-fight-ebola/, http://www.piaschile.cl/mercado/benchmarking-internacional/, https://shiny.tradestatistics.io/dashboard/ - El gráfico no solo se puede _ver_ (output) también, con conocimiento suficiente, poder usarlo como input --- # Revisemos un ejemplo simple .font150[ <br> Pero no por eso FOME! Revisemos el archivo `R/07-maps.R` ] --- class: clear, middle, right background-image: url("img/html.png") background-size: cover # <span style="background-color:#202020">htmlwidgets</span> --- # Esto no termina aquí (a menos que no te haya gustado la _interactivdad_) Highcharter es solo uno de muchos otros paquetes (http://gallery.htmlwidgets.org/) para aceder a las bondades ~~y dolores de cabeza~~ de html/javascript. Existe muchas librerías javascripts. Ploty es muy conocido pero existen muy muy buenas otras opciones: - [echarts4r](https://echarts4r.john-coene.com/) de [John (JP) Coene](https://twitter.com/jdatap), - [aperxcharter](https://dreamrs.github.io/apexcharter/articles/starting-with-apexcharts.html) y [billboarder](https://dreamrs.github.io/billboarder/articles/billboarder.html) de [Victor Perrier](https://twitter.com/_pvictorr) John y Victor tienen más paquetes tanto para visualización como shiny Como cada librería JS tiene su propia sintaxis el paquete R se desarrolla en función de dicha forma, pero muy son similares en cuanto a uso --- # Créditos y gracias totales ## Personas importantes! Patricia, Elio, Ignacio, Riva! La comunidad y desarrolladores (desde R a JS) ## Logo Mauricio @pacha Vargas ## Imágenes https://500px.com/photo/43752970/Mount-Fitzroy-at-sunset-by-Jimmy-Mcintyre