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# Gráficos dinâmicos
* <http://ouzor.github.io/blog/2014/11/21/interactive-visualizations.html>
## googleVis
* A galeria de gráficos do Google: [Google Charts Gallery].
* Repositório de desenvolvimento do googleVis:
[Markus Gesmann googleVis].
* Slides do autor: [Introduction to googleVis].
* Exemplos de uso do googleVis: [googleVis examples].
* Exemplos do [João Neto].
* A [vignette em pdf].
O pacote [googleVis] permite fazer gráficos da galeria Google Charts de
dentro do R. O deselvolvedor do pacote, Markus Gesmann, mantém o pacote
aberto no GitHub.
As funções do googleVis possuem o prefixo `gvis` e o restante é composto
pelo nome do gráfico na galeria Google com as letras maiúsculas e sem
espaços. Não existe uma correspondência um para um.
Todos os gráficos recebem objetos de classe `data.frame`. Todos os
aspectos gráficos são controlados dentro de uma lista para o argumento
`options=`. No entanto, a forma de modificar aspectos gráficos não segue
os padrões R mas as definições em javascript.
Os exemplos abaixo ilustram como usar algumas das funções do pacote e
modificar elementos gráficos.
```{r setOptions, message=FALSE}
library(googleVis)
## Para que output das funções gvis* não sejam páginas autocontidas mas
## os fragmentos mínimos para produzir os gráficos.
op <- options(gvis.plot.tag="chart")
## Funções gráficas do pacote googleVis.
apropos(what="^gvis", mode="function")
```
### Exemplos
Exemplo com o data frame `woman`.
```{r, results="asis", tidy=FALSE}
## Diagrama de dispesão.
Scatter <- gvisScatterChart(
women,
options=list(
legend="none",
vAxis="{title:'weight (lbs)'}",
hAxis="{title:'height (in)'}",
width=800, height=600))
plot(Scatter)
```
Para saber o que pode ser modificado, visitar a documentação de cada
tipo de gráfico na galeria do Google. A documentação do
[ScatterChart]. Abaixo um exemplo com o data frame `cars`.
```{r ScatterChart, results="asis", tidy=FALSE}
Scatter <- gvisScatterChart(
cars,
options=list(
gvis.editor="Edit me!",
explorer="{actions: ['dragToZoom', 'rightClickToReset'],
maxZoomIn:0.05}",
legend="none",
colors="['green']",
pointShape="square",
pointSize=5,
vAxis="{title:'Distance',
titleTextStyle:{color:'red', italic:false},
minValue:0, maxValue:130}",
hAxis="{title:'Speed',
titleTextStyle:{color:'blue'},
minValue:3, maxValue:26}",
width=800, height=600))
## Plot retorna o código HTML para o gráfico.
plot(Scatter)
```
Gráfico de barras com o data frame `HairEyeColor`.
```{r BarChart, results="asis", tidy=FALSE}
## str(HairEyeColor)
x <- apply(HairEyeColor, 1, sum)
H <- data.frame(hair=names(x), sum=x)
H$share <- H$sum/sum(H$sum)
Bar <- gvisBarChart(data=H, yvar="sum", xvar="hair",
options=list(
hAxis="{title:'Frequência absoluta'}",
vAxis="{title:'Cor de cabelo'}",
colors="['yellow']",
width=800, height=600))
plot(Bar)
Column <- gvisColumnChart(data=H, yvar="share", xvar="hair",
options=list(
hAxis="{title:'Cor de cabelo'}",
vAxis="{title:'Frequência relativa'}",
colors="['orange']",
width=800, height=600))
plot(Column)
```
```{r Candle, results="asis", tidy=FALSE}
x <- boxplot(Sepal.Length~Species, data=iris, outline=FALSE, plot=FALSE)
x <- data.frame(t(x$stats[-3,]))
names(x) <- c("Low", "Open", "Close", "High")
x <- cbind(Species=levels(iris$Species), x)
Candle <- gvisCandlestickChart(
data=x,
options=list(
legend="none",
hAxis="{title:'Espécies'}",
vAxis="{title:'Comprimento da pétala'}",
colors="['#123654']",
width=800, height=600))
plot(Candle)
```
Gŕafico de setores.
```{r Pie, results="asis", tidy=FALSE}
## str(HairEyeColor)
x <- apply(HairEyeColor, 2, sum)
H <- data.frame(eyes=names(x), sum=x)
H$share <- H$sum/sum(H$sum)
Pie <- gvisPieChart(
data=H, labelvar="eyes", numvar="sum",
options=list(
colors="['#7F462C', '#1569C7', '#C68E17', '#008000']",
width=800, height=600))
plot(Pie)
```
População dos Estados brasileiros:
<https://pt.wikipedia.org/wiki/Lista_de_unidades_federativas_do_Brasil_por_população>.
```{r GeoChart, results="asis", tidy=FALSE}
##----------------------------------------------------------------------
## Código do Web Scraping.
## library(XML)
## url <- "https://pt.wikipedia.org/wiki/Lista_de_unidades_federativas_do_Brasil_por_população"
## rl <- readLines(url)
## da <- readHTMLTable(rl, stringsAsFactors=FALSE)
## str(da)
## br <- da[[1]]
## br$Estado <- substr(br$Estado, 2, 20)
## br$População <- as.integer(gsub("\\D", "", br$População))
## dput(br[, c("Estado", "População")])
##----------------------------------------------------------------------
br <- data.frame(
Estado = c("São Paulo", "Minas Gerais", "Rio de Janeiro", "Bahia",
"Rio Grande do Sul", "Paraná", "Pernambuco", "Ceará",
"Pará", "Maranhão", "Santa Catarina", "Goiás", "Paraíba",
"Amazonas", "Espírito Santo", "Rio Grande do Norte",
"Alagoas", "Mato Grosso", "Piauí", "Distrito Federal",
"Mato Grosso do Sul", "Sergipe", "Rondônia", "Tocantins",
"Acre", "Amapá", "Roraima"),
População = c(44396484L, 20869101L, 16550024L, 15203934L, 11247972L,
11163018L, 9345173L, 8904459L, 8175113L, 6904241L,
6819190L, 6610681L, 3972202L, 3938336L, 3929911L,
3442175L, 3340932L, 3270973L, 3204028L, 2914830L,
2651235L, 2242937L, 1768204L, 1515126L, 803513L,
766679L, 505665L))
br$População <- log10(br$População)
breaks <- seq(floor(min(br$População)),
ceiling(max(br$População)), by=0.5)
require(RColorBrewer)
pal <- brewer.pal(n=length(breaks), name="Blues")
cl <- paste("{values:[",
paste0("'", formatC(breaks, format="d"), "'", collapse=","),
"], colors:[",
paste0("'", pal, "'", collapse=","),
"]}")
GeoStates <- gvisGeoChart(
data=br,
locationvar="Estado",
colorvar="População",
options=list(
title="lala",
region="BR",
displayMode="regions",
resolution="provinces",
colorAxis=cl,
width=600, height=400))
plot(GeoStates)
```
```{r MapChart, results="asis", tidy=FALSE}
##----------------------------------------------------------------------
## Código do Web Scraping.
## library(XML)
## url <- "http://relogiosdesol.blogspot.com.br/2009/11/coordenadas-geograficas-das-capitas-dos.html"
## rl <- readLines(url)
## da <- readHTMLTable(rl, stringsAsFactors=FALSE)
## br <- da[[1]][-1,]
## names(br) <- c("capital", "lat", "lon")
##----------------------------------------------------------------------
br <- data.frame(
capital = c("Aracaju - SE", "Belém - PA", "Belo Horizonte - MG",
"Boa Vista - RR", "Brasília - DF", "Campo Grande - MS",
"Cuiabá - MT", "Curitiba - PR", "Florianópolis - SC",
"Fortaleza - CE", "Goiânia - GO", "João Pessoa - PB",
"Macapá - AP", "Maceió - AL", "Manaus - AM",
"Natal - RN", "Palmas - TO", "Porto Alegre - RS",
"Porto Velho - RO", "Recife - PE", "Rio Branco - AC",
"Rio de Janeiro - RJ", "Salvador - BA", "São Luís - MA",
"São Paulo - SP", "Teresina - PI", "Vitória - ES"),
lat = c(-10.911, -1.456, -19.921, 2.82, -15.78, -20.443, -15.596,
-25.428, -27.597, -3.717, -16.679, -7.115, 0.039, -9.666,
-3.102, -5.795, -10.213, -30.033, -8.762, -8.054, -9.975,
-22.903, -12.971, -2.53, -23.548, -5.089, -20.319),
lon = -c(37.072, 48.504, 43.938, 60.673, 47.93, 54.646, 56.097,
49.273, 48.549, 38.543, 49.254, 34.863, 51.066, 35.735,
60.025, 35.209, 48.36, 51.23, 63.904, 34.881, 67.81,
43.208, 38.511, 44.303, 46.636, 42.802, 40.338))
br$latlon <- with(br, paste(lat, lon, sep=":"))
Map <- gvisMap(br,
locationvar="latlon",
tipvar="capital",
options=list(showTip=TRUE,
showLine=TRUE,
enableScrollWheel=TRUE,
mapType='terrain',
useMapTypeControl=TRUE,
width="800px",
height="800px"))
plot(Map)
```
Dados de precipitação de Dourados em 2014 extratídos da Embrapa CPAO:
<http://www.cpao.embrapa.br/clima/?lc=site/banco-dados/base_dados>.
```{r}
dourados <- data.frame(
dias=seq(from=as.Date("2014-01-01"),
to=as.Date("2014-12-31"), by=1),
chuva=c(0.2, 0.0, 3.6, 32.0, 38.2, 2.8, 0.0, 44.8, 0.0, 0.8, 1.0,
2.0, 23.0, 37.4, 1.0, 0.2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 61.6, 0.0, 0.2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.8, 0.0, 0.0, 0.2, 0.0, 6.8, 0.0, 0.0, 31.6, 3.6, 3.8, 0.0,
0.0, 0.0, 0.0, 0.0, 44.4, 17.6, 3.6, 0.2, 5.0, 28.2, 20.2,
0.2, 0.0, 0.0, 13.2, 2.8, 0.0, 0.0, 1.8, 0.0, 0.0, 0.0,
17.0, 5.6, 0.6, 0.0, 20.2, 0.2, 0.6, 0.8, 0.0, 7.0, 11.2,
12.6, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.2, 1.6, 0.2, 0.4, 7.4,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 17.2, 1.4, 11.6,
4.2, 0.2, 1.0, 0.0, 0.0, 2.8, 0.4, 0.2, 12.8, 7.0, 0.2, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 45.2, 9.4, 0.2, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.2, 0.0, 0.0, 0.0, 0.0, 14.0, 0.4, 1.8, 0.2,
0.0, 0.0, 0.0, 27.4, 7.6, 7.6, 10.6, 0.2, 0.0, 0.0, 0.0,
0.0, 5.2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 27.6, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 7.6, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 10.8, 5.8, 8.6, 13.8, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 20.0, 3.0, 0.0, 0.0, 0.0, 0.0, 26.2, 15.2, 0.0, 2.2,
0.4, 3.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 5.2, 0.0, 0.0, 0.0, 0.2, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 15.6,
0.2, 0.0, 0.0, 0.0, 0.0, 0.0, 9.2, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 20.8, 2.2, 0.0, 0.0, 0.0,
29.8, 0.0, 4.2, 14.2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 5.2, 1.2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 32.2, 0.2, 0.0, 0.0, 35.4, 3.0, 0.0, 0.0,
0.0, 27.0, 9.2, 0.0, 3.4, 0.0, 0.0, 6.2, 0.0, 3.8, 0.0,
32.4, 0.0, 0.0, 27.4, 1.4, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 24.2, 50.8, 0.0, 0.4, 21.2, 0.0, 0.0, 0.0, 0.0,
6.4, 12.4, 0.6, 0.0, 0.0, 0.0, 0.0, 9.2, 9.4, 2.4, 1.8, 1.8,
22.0, 5.0, 0.0, 0.0, 0.0, 17.6, 0.0, 0.0, 0.8, 14.2, 10.2,
5.8, 0.0, 0.0, 2.2, 0.0, 0.0, 0.0, 2.8, 0.0),
tmax=c(30.2, 33.9, 34.0, 29.8, 33.4, 30.0, 32.8, 32.3, 31.7, 34.0,
34.9, 30.5, 29.8, 28.2, 28.2, 29.4, 31.3, 32.8, 33.5, 34.4,
33.2, 33.3, 32.5, 32.8, 27.0, 32.4, 32.5, 33.4, 34.0, 34.1,
35.6, 36.2, 36.3, 36.1, 35.2, 35.8, 37.9, 37.4, 37.9, 35.5,
35.7, 35.7, 32.9, 32.2, 27.9, 28.6, 28.9, 30.4, 31.7, 32.6,
31.4, 26.4, 29.7, 29.7, 30.1, 28.5, 28.9, 26.3, 29.7, 31.4,
33.0, 21.9, 29.9, 32.1, 32.3, 29.8, 31.6, 33.7, 23.3, 25.1,
30.2, 31.5, 32.0, 33.6, 33.3, 33.0, 32.5, 31.8, 28.8, 30.3,
26.3, 28.3, 29.1, 30.4, 30.2, 30.8, 30.9, 27.4, 29.7, 30.1,
30.5, 31.8, 31.5, 31.4, 32.3, 33.6, 34.5, 34.7, 34.5, 28.9,
27.6, 27.2, 21.3, 21.3, 19.3, 22.3, 30.9, 27.4, 29.9, 27.2,
29.3, 21.4, 27.0, 27.3, 27.2, 27.6, 27.0, 25.6, 28.4, 30.3,
19.7, 24.0, 28.7, 28.9, 24.8, 27.2, 29.1, 28.9, 26.6, 25.0,
25.2, 27.9, 25.9, 28.6, 26.8, 25.0, 26.3, 26.6, 28.8, 28.6,
30.5, 30.7, 18.7, 14.0, 15.2, 12.5, 17.6, 21.3, 23.1, 25.3,
29.0, 22.2, 20.8, 22.7, 26.6, 30.3, 29.8, 30.4, 25.9, 20.0,
21.3, 26.7, 28.2, 29.9, 24.3, 27.6, 29.1, 28.3, 25.7, 23.4,
23.2, 24.8, 24.7, 30.1, 30.2, 29.6, 30.7, 28.0, 14.7, 20.2,
21.2, 25.0, 29.1, 30.4, 31.5, 30.8, 22.1, 17.1, 18.1, 16.8,
20.3, 22.4, 25.3, 26.4, 27.1, 28.3, 30.7, 30.9, 21.2, 21.5,
23.9, 26.4, 29.6, 22.6, 18.5, 16.9, 17.1, 17.5, 20.6, 24.9,
28.0, 29.3, 31.1, 31.9, 32.5, 32.6, 30.5, 27.6, 31.1, 29.1,
27.5, 28.4, 30.8, 33.0, 22.2, 22.6, 23.1, 29.7, 25.6, 29.7,
31.4, 29.5, 32.6, 33.8, 34.6, 34.6, 33.0, 22.2, 21.9, 27.7,
31.3, 33.5, 35.8, 33.8, 34.7, 34.4, 31.1, 28.8, 35.8, 24.8,
30.6, 34.4, 35.4, 35.9, 35.5, 35.4, 36.3, 26.8, 28.1, 34.0,
36.7, 28.9, 23.9, 26.9, 29.7, 33.7, 26.2, 31.1, 33.8, 22.4,
32.0, 35.0, 35.0, 33.0, 31.0, 29.7, 28.8, 29.0, 30.8, 31.8,
35.4, 35.5, 37.1, 38.2, 38.2, 39.4, 39.0, 39.2, 39.7, 40.8,
38.6, 37.7, 23.2, 29.5, 31.0, 33.1, 30.6, 27.4, 30.8, 33.0,
33.7, 33.6, 33.9, 32.5, 29.5, 31.7, 32.6, 31.5, 31.8, 32.9,
32.7, 26.6, 31.2, 33.4, 32.0, 26.8, 30.1, 28.8, 29.7, 30.3,
31.1, 33.6, 33.5, 29.6, 32.9, 22.2, 29.4, 32.3, 30.0, 26.1,
31.6, 31.0, 30.4, 32.5, 30.3, 26.4, 25.4, 30.3, 29.6, 31.1,
32.0, 30.3, 29.9, 31.9, 30.5, 30.8, 31.1, 32.9, 31.9, 31.8,
30.3, 29.2, 32.8, 32.9, 31.9, 24.0, 29.5, 26.7, 32.2, 32.5,
34.0, 34.8, 34.9, 33.2, 32.5),
tmin=c(23.5, 22.4, 21.8, 20.1, 19.0, 19.1, 20.1, 19.1, 19.1, 19.6,
21.1, 20.6, 18.9, 17.7, 20.6, 19.4, 19.0, 17.3, 20.3, 20.1,
21.8, 20.9, 22.6, 22.3, 18.8, 18.5, 18.6, 20.2, 19.5, 19.7,
20.5, 19.9, 21.1, 20.4, 22.4, 21.0, 21.1, 22.9, 21.3, 20.6,
21.2, 21.6, 19.6, 21.6, 20.5, 20.4, 19.5, 23.4, 21.4, 21.9,
21.1, 20.7, 21.2, 20.4, 20.5, 19.7, 19.5, 17.5, 16.0, 16.0,
18.5, 18.1, 18.6, 19.9, 20.1, 19.5, 17.9, 18.0, 17.7, 17.2,
18.5, 19.9, 18.3, 20.7, 19.9, 21.1, 19.4, 22.1, 20.7, 21.2,
17.7, 14.0, 18.2, 18.8, 18.4, 17.9, 19.5, 21.0, 21.1, 20.7,
18.7, 19.2, 19.5, 19.4, 20.7, 21.5, 21.4, 23.6, 19.9, 20.1,
20.5, 19.3, 14.4, 11.5, 14.6, 16.6, 15.6, 16.7, 16.1, 16.7,
17.7, 17.2, 16.0, 16.1, 13.6, 13.8, 17.1, 14.6, 15.4, 16.4,
13.5, 12.3, 15.8, 17.8, 18.0, 17.0, 14.5, 16.9, 13.7, 10.4,
13.7, 13.5, 16.5, 18.1, 16.3, 16.0, 12.9, 13.7, 14.1, 15.2,
17.8, 18.3, 10.9, 10.4, 8.9, 8.3, 8.0, 4.9, 8.0, 12.8, 15.8,
10.4, 7.5, 6.2, 14.8, 20.7, 21.9, 21.9, 14.9, 12.3, 13.8,
14.6, 16.9, 17.8, 17.6, 17.0, 16.8, 16.1, 15.2, 12.3, 9.8,
11.3, 11.7, 14.0, 17.4, 15.0, 17.4, 13.8, 12.5, 9.3, 7.2,
8.7, 14.3, 15.2, 16.6, 15.0, 13.4, 12.7, 12.7, 14.3, 13.8,
12.5, 12.1, 13.3, 14.1, 14.5, 15.8, 15.5, 9.5, 6.2, 5.9,
10.0, 13.8, 17.0, 6.4, 6.3, 11.1, 11.0, 15.1, 13.4, 14.4,
14.6, 12.8, 16.0, 16.0, 13.7, 16.0, 15.1, 15.0, 14.6, 13.3,
14.3, 14.3, 15.9, 10.5, 6.4, 13.0, 14.3, 16.5, 15.0, 15.1,
14.5, 13.2, 14.3, 17.0, 18.5, 14.4, 10.6, 10.0, 10.4, 13.1,
16.2, 18.5, 17.8, 22.1, 20.5, 18.5, 16.0, 17.5, 17.7, 16.0,
20.2, 18.4, 18.0, 17.2, 18.3, 19.5, 14.0, 11.7, 14.9, 20.3,
19.1, 16.6, 13.0, 10.8, 16.5, 17.6, 17.6, 18.8, 18.5, 18.5,
20.6, 19.9, 21.5, 19.2, 14.8, 14.3, 14.0, 16.4, 16.1, 18.5,
19.9, 17.4, 20.5, 21.9, 21.8, 23.0, 22.8, 22.4, 23.4, 24.1,
21.6, 18.3, 16.8, 17.8, 18.0, 18.9, 18.7, 19.7, 19.3, 21.4,
22.0, 20.4, 20.1, 20.9, 19.6, 21.2, 20.5, 19.8, 22.3, 19.8,
18.8, 17.7, 19.0, 18.3, 18.1, 17.9, 16.8, 14.6, 15.6, 16.5,
15.8, 20.6, 19.9, 21.1, 17.7, 16.4, 20.7, 20.8, 20.3, 21.1,
20.4, 20.7, 21.6, 21.1, 19.5, 19.3, 19.3, 20.7, 20.2, 18.6,
18.8, 19.9, 20.5, 20.9, 21.0, 19.9, 21.1, 21.2, 21.0, 19.6,
19.3, 21.2, 22.0, 22.3, 19.8, 18.1, 19.9, 21.2, 22.6, 21.6,
22.7, 21.7, 21.2, 22.8))
```
```{r Serie, results="asis", tidy=FALSE}
Serie <- gvisLineChart(
data=dourados,
xvar="dias",
yvar=c("tmin", "tmax"),
options=list(
hAxis="{title:'Dias em 2014'}",
vAxis="{title:'Temperatura (Celsius)'}",
width=800, height=400))
plot(Serie)
```
Para ver o gráfico abaixo adequadamente, você tem que configurar como
local do seu sistema operacional um ponto que não tenha horário de
verão. Por exemplo, usar Bahia ao invés de Curitiba nas definições de
*Time & Date* do Linux. Veja essa série de mensagens para maiores
detalhes: [googleVis/issue#15].
```{r Calendar, results="asis", tidy=FALSE}
Cal <- gvisCalendar(
dourados,
datevar="dias",
numvar="chuva",
options=list(
title="Precipitação diária em Dourados-MS",
width=1000, height=300,
calendar="{cellSize: 15,
cellColor:{stroke: 'red', strokeOpacity: 0.2},
focusedCellColor:{stroke: 'red'}}")
)
plot(Cal)
```
[googleVis]: https://cran.r-project.org/web/packages/googleVis/index.html
[Markus Gesmann googleVis]: https://github.com/mages/googleVis
[Introduction to googleVis]: http://mages.github.io/Introduction_to_googleVis/
[Google Charts Gallery]: https://developers.google.com/chart/interactive/docs/gallery
[googleVis examples]: https://cran.r-project.org/web/packages/googleVis/vignettes/googleVis_examples.html
[ScatterChart]: https://google-developers.appspot.com/chart/interactive/docs/gallery/scatterchart
[João Neto]: http://www.di.fc.ul.pt/~jpn/r/GraphicalTools/googleVis.html
[vignette em pdf]: https://cran.r-project.org/web/packages/googleVis/vignettes/googleVis.pdf
[googleVis/issue#15]: https://github.com/mages/googleVis/issues/15
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