google_charts: Google Charts

google_chartsR Documentation

Google Charts

Description

Google Charts can be displayed inside an info_window

info_window

When using a chart in an info_window you need to use a list with at least two elements named data and type. You can also use a third element called options for controlling the appearance of the chart.

You must also supply the id argument to the layer your are adding (e.g. add_markers()), and the data must have a column with the same name as the id (and therefore the same name as the id column in the original data supplied to the add_ function).

See the specific chart sections for details on how to structure the data.

chart types

the type element can be one of

  • area

  • bar

  • bubble

  • candlestick

  • column

  • combo

  • histogram

  • line

  • pie

  • scatter

Area

data

An area chart requires a data.frame of at least three columns:

  1. First column: a column of id values, where the column has the same name as the id column in the data argument, and therefore the same name as the value supplied to the id argument.

  2. Second column: variable names used for labelling the data

  3. Third or more columns: the data used in the chart

type - area

options see the area charts documentation for various other examples https://developers.google.com/chart/interactive/docs/gallery/areachart

Each row of data represents a data point at the same x-axis location

Bar

data

A bar chart requires a data.frame of at least three columns:

  1. First column: a column of id values, where the column has the same name as the id column in the data argument, and therefore the same name as the value supplied to the id argument.

  2. Second column: variable names used for labelling the data

  3. Third or more columns: the data used in the chart

type - bar

options

See the bar chart documentation for various other examples https://developers.google.com/chart/interactive/docs/gallery/barchart

Bubble

data

A bubble chart requires a data.frame of at least four, and at most six columns:

  1. First column: a column of id values, where the column has the same name as the id column in the data argument, and therefore the same name as the value supplied to the id argument.

  2. Second column: variable names used for labelling the data

  3. Third column: x-axis value

  4. Fourth column: y-axis value

  5. Fith column: visualised as colour

  6. Sixth column: visualised as size

type - bubble

options

See the bubble chart documentation for various other examples https://developers.google.com/chart/interactive/docs/gallery/bubblechart

Candlestick

data

A candlestick chart requires a data.frame of at least six columns:

  1. First column: a column of id values, where the column has the same name as the id column in the data argument, and therefore the same name as the value supplied to the id argument.

  2. Second column: variable names used for labelling the data

  3. Third column: Number specifying the 'low' number for the data

  4. Fourth column: Number specifying the opening/initial value of the data. This is one vertical border of the candle. If less than the column 4 value, the candle will be filled; otherwise it will be hollow.

  5. Fith column: Number specifying the closing/final value of the data. This is the second vertical border of the candle. If less than the column 3 value, the candle will be hollow; otherwise it will be filled.

  6. Sixth column: Number specifying the high/maximum value of this marker. This is the top of the candle's center line.

type - candlestick

options

See the candlestick chart documentation for various other examples https://developers.google.com/chart/interactive/docs/gallery/candlestickchart

Column

data

A column chart requires a data.frame of at least three columns:

  1. First column: a column of id values, where the column has the same name as the id column in the data argument, and therefore the same name as the value supplied to the id argument.

  2. Second column: variable names used for labelling the data

  3. Third or more columns: the data used in the chart

type - column

options

See the column chart documentation for various other examples https://developers.google.com/chart/interactive/docs/gallery/columnchart

Combo

A combo chart lets you render each series as a different marker type from the following list: line, area, bars, candlesticks, and stepped area.

data

A combo chart requires a data.frame of at least three columns:

  1. First column: a column of id values, where the column has the same name as the id column in the data argument, and therefore the same name as the value supplied to the id argument.

  2. Second column: variable names used for labelling the data

  3. Third or more columns: the data used in the chart

type - combo

options

See the column chart documentation for various other examples https://developers.google.com/chart/interactive/docs/gallery/combochart

Histogram

data

A histogram chart requires a data.frame of at least three columns:

  1. First column: a column of id values, where the column has the same name as the id column in the data argument, and therefore the same name as the value supplied to the id argument.

  2. Second column: variable names used for labelling the data

  3. Third or more columns: the data used in the chart

type - histogram

options

See the histogram chart documentation for various other examples https://developers.google.com/chart/interactive/docs/gallery/histogram

Line

data

A line chart requires a data.frame of at least three columns:

  1. First column: a column of id values, where the column has the same name as the id column in the data argument, and therefore the same name as the value supplied to the id argument.

  2. Second column: variable names used for labelling the data

  3. Third or more columns: the data used in the chart

type - line

options

See the line chart documentation for various other examples https://developers.google.com/chart/interactive/docs/gallery/linechart

Pie

data

A pie chart requires a data.frame of three columns:

  1. First column: a column of id values, where the column has the same name as the id column in the data argument, and therefore the same name as the value supplied to the id argument.

  2. Second column: variable names used for labelling the data

  3. Third column: the data used in the chart

type - pie

options

See the pie chart documentation for various other examples https://developers.google.com/chart/interactive/docs/gallery/piechart

Scatter

data

A scatter chart requires a data.frame of at least four columns:

  1. First column: a column of id values, where the column has the same name as the id column in the data argument, and therefore the same name as the value supplied to the id argument.

  2. Second column: variable names used for labelling the data

  3. Third column: the data plotted on x-axis

  4. Fourth or more columns: the data plotted on y-axis

type - scatter

options

See the scatter chart documentation for various other examples https://developers.google.com/chart/interactive/docs/gallery/scatterchart

Examples

## Not run: 

set_key("your_api_key")

## AREA
markerCharts <- data.frame(stop_id = rep(tram_stops$stop_id, each = 2),
    year = rep( c("year1", "year2")),
    arrivals = sample(1:100, size = nrow(tram_stops) * 2, replace = T),
    departures = sample(1:100, size = nrow(tram_stops) * 2, replace = T))

chartList <- list(data = markerCharts,
   type = 'area',
   options = list(width = 400, chartArea = list(width = "50%")))

google_map() %>%
  add_markers(data = tram_stops, info_window = chartList, id = "stop_id")

tram_route$id <- c(rep(1, 30), rep(2, 25))

lineCharts <- data.frame(id = rep(c(1,2), each = 2),
    year = rep( c("year1", "year2") ),
    arrivals = sample(1:100, size = 4),
    departures = sample(1:100, size = 4))

chartList <- list(data = lineCharts,
   type = 'area')

google_map() %>%
  add_polylines(data = tram_route, id = 'id',
    stroke_colour = "id", stroke_weight = 10,
    lat = "shape_pt_lat", lon = "shape_pt_lon",
    info_window = chartList
    )


## End(Not run)

## Not run: 

## BAR
markerCharts <- data.frame(stop_id = rep(tram_stops$stop_id, each = 2),
    year = rep( c("year1", "year2")),
    arrivals = sample(1:100, size = nrow(tram_stops) * 2, replace = T),
    departures = sample(1:100, size = nrow(tram_stops) * 2, replace = T))

chartList <- list(data = markerCharts,
   type = 'bar')

google_map() %>%
  add_markers(data = tram_stops, info_window = chartList, id = "stop_id")


lineChart <- data.frame(id = 33,
    year = c("year1","year2"),
    val1 = c(1,2),
    val2 = c(2,1))

chartList <- list(data = lineChart, type = 'bar')

google_map() %>%
  add_polylines(data = melbourne[melbourne$polygonId == 33, ],
  polyline = "polyline",
  info_window = chartList)


## End(Not run)


## Not run: 

## BUBBLE
markerCharts <- data.frame(stop_id = rep(tram_stops$stop_id, each = 4),
    ID = sample(letters, size = nrow(tram_stops) * 4, replace = T),
    time = sample(1:1440, size = nrow(tram_stops) * 4, replace = T),
    passengers = sample(1:100, size = nrow(tram_stops) * 4, replace = T),
    year = c("year1", "year2", "year3", "year4"),
    group = sample(50:100, size = nrow(tram_stops) * 4, replace = T))

chartList <- list(data = markerCharts,
   type = 'bubble')

google_map() %>%
  add_markers(data = tram_stops, info_window = chartList, id = "stop_id")


## End(Not run)

## Not run: 

## CANDLESTICK
markerCharts <- data.frame(stop_id = rep(tram_stops$stop_id, each = 5),
    day = rep(c("Mon", "Tues", "Weds", "Thurs", "Fri"), times = nrow(tram_stops) ),
    val1 = rep(c(20, 31, 50, 77, 68), times = nrow(tram_stops) ),
    val2 = rep(c(28, 38, 55, 77, 66), times = nrow(tram_stops) ),
    val3 = rep(c(38, 55, 77, 66, 22), times = nrow(tram_stops) ),
    val4 = rep(c(45, 66, 80, 50, 15), times = nrow(tram_stops) ) )

chartList <- list(data = markerCharts,
   type = 'candlestick',
   options = list(legend = 'none',
     bar = list(groupWidth = "100%"),
     candlestick = list(
       fallingColor = list( strokeWidth = 0, fill = "#a52714"),
       risingColor = list( strokeWidth = 0, fill = "#0f9d58")
       )
     ))

google_map() %>%
  add_markers(data = tram_stops, info_window = chartList, id = "stop_id")


## End(Not run)


## Not run: 

## COLUMN
markerCharts <- data.frame(stop_id = rep(tram_stops$stop_id, each = 2),
    year = rep( c("year1", "year2")),
    arrivals = sample(1:100, size = nrow(tram_stops) * 2, replace = T),
    departures = sample(1:100, size = nrow(tram_stops) * 2, replace = T))

chartList <- list(data = markerCharts,
   type = 'column')

google_map() %>%
  add_markers(data = tram_stops, info_window = chartList, id = "stop_id")

polyChart <- data.frame(id = 33,
    year = c("year1","year2"),
    val1 = c(1,2),
    val2 = c(2,1))

chartList <- list(data = polyChart, type = 'column')

google_map() %>%
  add_polygons(data = melbourne[melbourne$polygonId == 33, ],
  polyline = "polyline",
  info_window = chartList)

tram_route$id <- 1

polyChart <- data.frame(id = 1,
    year = c("year1","year2"),
    val1 = c(1,2),
    val2 = c(2,1))

chartList <- list(data = polyChart, type = 'column')

google_map() %>%
  add_polygons(data = tram_route,
    lon = "shape_pt_lon", lat = "shape_pt_lat",
    info_window = chartList)



## End(Not run)

## Not run: 


## COMBO
markerCharts <- data.frame(stop_id = rep(tram_stops$stop_id, each = 2),
    year = rep( c("year1", "year2")),
    arrivals = sample(1:100, size = nrow(tram_stops) * 2, replace = T),
    departures = sample(1:100, size = nrow(tram_stops) * 2, replace = T))

markerCharts$val <- sample(1:100, size = nrow(markerCharts), replace = T)

chartList <- list(data = markerCharts,
   type = 'combo',
   options = list(
     "title" = "Passengers at stops",
     "vAxis" = list( title = "passengers" ),
     "hAxis" = list( title = "load" ),
     "seriesType" = "bars",
     "series" = list( "2" = list( "type" = "line" )))) ## 0-indexed

google_map() %>%
  add_circles(data = tram_stops, info_window = chartList, id = "stop_id")


## End(Not run)


## Not run: 

## HISTOGRAM
markerCharts <- data.frame(stop_id = rep(tram_stops$stop_id, each = 20),
    day = as.character(1:20))

markerCharts$wait <- rnorm(nrow(markerCharts), 0, 1)

chartList <- list(data = markerCharts,
   type = 'histogram')

google_map() %>%
  add_circles(data = tram_stops, info_window = chartList, id = "stop_id")


## End(Not run)


## Not run: 

## Line
markerCharts <- data.frame(stop_id = rep(tram_stops$stop_id, each = 20),
    day = as.character(1:20),
    value = sample(1:100, size = nrow(tram_stops) * 20, replace = T))

chartList <- list(data = markerCharts,
   type = 'line')

google_map() %>%
  add_circles(data = tram_stops, info_window = chartList, id = "stop_id")


## End(Not run)


## Not run: 

## PIE
markerCharts <- data.frame(stop_id = rep(tram_stops$stop_id, each = 3))
markerCharts$variable <- c("yes", "no", "maybe")
markerCharts$value <- sample(1:10, size = nrow(markerCharts), replace = T)

chartList <- list(data = markerCharts,
   type = 'pie',
   options = list(title = "my pie",
     is3D = TRUE,
     height = 240,
     width = 240,
     colors = c('#440154', '#21908C', '#FDE725')))

google_map() %>%
  add_markers(data = tram_stops, info_window = chartList, id = "stop_id")

## use pieHole option to make a donut chart

chartList <- list(data = markerCharts,
   type = 'pie',
   options = list(title = "my pie",
     pieHole = 0.4,
     height = 240,
     width = 240,
     colors = c('#440154', '#21908C', '#FDE725')))

google_map() %>%
  add_markers(data = tram_stops, info_window = chartList, id = "stop_id")


## End(Not run)


## Not run: 

## SCATTER
markerCharts <- data.frame(stop_id = rep(tram_stops$stop_id, each = 5))
markerCharts$arrival <- sample(1:10, size = nrow(markerCharts), replace = T)
markerCharts$departure <- sample(1:10, size = nrow(markerCharts), replace = T)

chartList <- list(data = markerCharts,
   type = 'scatter')

google_map() %>%
  add_markers(data = tram_stops, info_window = chartList, id = "stop_id")

## End(Not run)



googleway documentation built on March 18, 2022, 7:34 p.m.