Google Histogram Chart with R \Sexpr{googleChartName <- "histogram"} \Sexpr{gvisChartName <- "gvisHistogram"}

Share:

Description

The gvisHistogram function reads a data.frame and creates text output referring to the Google Visualisation API, which can be included into a web page, or as a stand-alone page. The actual chart is rendered by the web browser using SVG or VML.

Usage

1
gvisHistogram(data, options = list(), chartid)

Arguments

data

a data.frame to be displayed as a histogram. Each column will be displayed as a histogram.

options

list of configuration options, see

\Sexpr[results=rd]{gsub("CHARTNAME", googleChartName, readLines(file.path(".", "inst", "mansections", "GoogleChartToolsURLConfigOptions.txt")))} \Sexpr[results=rd]{paste(readLines(file.path(".", "inst", "mansections", "gvisOptions.txt")))}
chartid

character. If missing (default) a random chart id will be generated based on chart type and tempfile.

Value

\Sexpr[results=rd]{paste(gvisChartName)}

returns list of class \Sexpr[results=rd]{paste(readLines(file.path(".", "inst", "mansections", "gvisOutputStructure.txt")))}

Author(s)

Markus Gesmann markus.gesmann@gmail.com,

Diego de Castillo decastillo@gmail.com

References

Google Chart Tools API: \Sexpr[results=rd]{gsub("CHARTNAME", googleChartName, readLines(file.path(".", "inst", "mansections", "GoogleChartToolsURL.txt")))}

See Also

See also print.gvis, plot.gvis for printing and plotting methods

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
## Please note that by default the googleVis plot command
## will open a browser window and requires an internet
## connection to display the visualisation.


hist1 <- gvisHistogram(dino)
plot(hist1)

## Histogram of the top 20 countries
pop <- Population[1:20,c("Country", "Population")]
pop=transform(pop, Population=round(Population/1e6))

hist2 <- gvisHistogram(pop, option=list(title="Country Populations",
                                    legend="{ position: 'none' }",
                                    colors="['green']"))
plot(hist2)
                                    
set.seed(123)
dat=data.frame(A=rpois(100, 20), 
               B=rpois(100, 5), 
               C=rpois(100, 50))
hist3 <- gvisHistogram(dat, options=list(
                       legend="{ position: 'top', maxLines: 2 }",
                       colors="['#5C3292', '#1A8763', '#871B47']"))

plot(hist3)

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.