R: Convenience Functions for Plotting zoo Objects with ggplot2

ggplot2.zoo {zoo}

R Documentation

Convenience Functions for Plotting zoo Objects with ggplot2

Description

fortify.zoo takes a zoo object and converts it into a data frame (intended for ggplot2). autoplot.zoo takes a zoo object and returns a ggplot2 object. It essentially uses the mapping aes(x = Time, y = Value, group = Series) and adds colour = Series in the case of a multivariate series with facets = NULL.

Usage

  ## S3 method for class 'zoo'
autoplot(object, geom = "line", facets, ...)
  ## S3 method for class 'zoo'
fortify(model, data, 
	names = c("Index", "Series", "Value"),
	melt = FALSE, sep = NULL, ...)
  facet_free(facets = Series ~ ., margins = FALSE, scales = "free_y", ...)

  yearmon_trans(format = "%b %Y", n = 5)
  scale_x_yearmon(..., format = "%b %Y", n = 5)
  scale_y_yearmon(..., format = "%b %Y", n = 5)

  yearqtr_trans(format = "%Y-%q", n = 5)
  scale_x_yearqtr(..., format = "%Y-%q", n = 5)
  scale_y_yearqtr(..., format = "%Y-%q", n = 5)

Arguments

`object`	an object of class `"zoo"`.
`geom`	character (e.g., `"line"`) or function (e.g., `geom_line`) specifying which `geom` to use.
`facets`	specification of `facets` for `facet_grid`. The default in the `autoplot` method is to use `facets = NULL` for univariate series and `facets = Series ~ .` for multivariate series.
`...`	further arguments passed to `aes` for `autoplot` (e.g., `linetype = Series` and/or `shape = Series`). For `fortify` the arguments are not used. For the `scale__` functions the arguments are passed on to `scale_*_continuous`.
`model`	an object of class `"zoo"` to be converted to a `"data.frame"`.
`data`	not used (required by generic `fortify` method).
`names`	(list of) character vector(s). New names given to index/time column, series indicator (if melted), and value column (if melted). If only a subset of characters should be changed, either NAs can be used or a named vector.
`sep`	If specified then the Series column is split into multiple columns using sep as the split character.
`melt`	Should the resulting data frame be in long format (`melt = TRUE`) or wide format (`melt = FALSE`).
`margins`	As in `facet_grid`.
`scales`	As in `facet_grid` except it defaults to `"free_y"`.
`format`	A format acceptable to format.yearmon or format.yearqtr.
`n`	Approximate number of axis ticks.

Details

Convenience interface for visualizing zoo objects with ggplot2. autoplot.zoo uses fortify.zoo (with melt = TRUE) to convert the zoo object into a data frame and then uses a suitable aes() mapping to visiualize the series.

Value

fortify.zoo returns a data.frame either in long format (melt = TRUE) or in wide format (melt = FALSE). The long format has three columns: the time Index, a factor indicating the Series, and the corresponding Value. The wide format simply has the time Index plus all columns of coredata(model).

autoplot.zoo returns a ggplot object.

Author(s)

Trevor L. Davis trevor.l.davis@gmail.com, Achim Zeileis

Examples

if(require("ggplot2") && require("scales")) {
suppressWarnings(RNGversion("3.5.0"))
set.seed(1)

## example data
x.Date <- as.Date(paste(2003, 02, c(1, 3, 7, 9, 14), sep = "-"))
x <- zoo(rnorm(5), x.Date)
xlow <- x - runif(5)
xhigh <- x + runif(5)
z <- cbind(x, xlow, xhigh)

## univariate plotting
autoplot(x)
## by hand
ggplot(aes(x = Index, y = Value), data = fortify(x, melt = TRUE)) +
  geom_line() + xlab("Index") + ylab("x")
## adding series one at a time
last_plot() + geom_line(aes(x = Index, y = xlow), colour = "red", data = fortify(xlow))
## add ribbon for high/low band
ggplot(aes(x = Index, y = x, ymin = xlow, ymax = xhigh), data = fortify(x)) +
  geom_ribbon(fill = "darkgray") + geom_line()

## multivariate plotting in multiple or single panels
autoplot(z)                      ## multiple without color/linetype
autoplot(z, facets = Series ~ .) ## multiple with series-dependent color/linetype
autoplot(z, facets = NULL)       ## single with series-dependent color/linetype
## by hand with color/linetype and with/without facets
ggz <- ggplot(aes(x = Index, y = Value, group = Series, colour = Series, linetype = Series),
  data = fortify(z, melt = TRUE)) + geom_line() + xlab("Index") + ylab("")
ggz
ggz + facet_grid(Series ~ .)
## variations
autoplot(z, geom = "point")
autoplot(z, facets = NULL) + geom_point()
autoplot(z, facets = NULL) + scale_colour_grey() + theme_bw()

## for "ts" series via coercion
autoplot(as.zoo(EuStockMarkets))
autoplot(as.zoo(EuStockMarkets), facets = NULL)

autoplot(z) + 
	aes(colour = NULL, linetype = NULL) +
	facet_grid(Series ~ ., scales = "free_y")

autoplot(z) + aes(colour = NULL, linetype = NULL) + facet_free() # same

z.yq <- zooreg(rnorm(50), as.yearqtr("2000-1"), freq = 4)
autoplot(z.yq)

## mimic matplot
data <- cbind(A = c(6, 1, NA, NA), B = c(16, 4, 1, NA), C = c(25, 7, 2, 1))
autoplot(zoo(data), facet = NULL) + geom_point()
## with different line types
autoplot(zoo(data), facet = NULL) + geom_point() + aes(linetype = Series)

## illustrate just fortify() method
z <- zoo(data)
fortify(z)
fortify(z, melt = TRUE)
fortify(z, melt = TRUE, names = c("Time", NA, "Data"))
fortify(z, melt = TRUE, names = c(Index = "Time"))

## with/without splitting
z <- zoo(cbind(a.A = 1:2, a.B = 2:3, b.A = 3:4, c.B = 4:5))
fortify(z)
fortify(z, melt = TRUE, sep = ".", names = list(Series = c("Lower", "Upper")))

## scale_x_yearmon with custom discrete breaks
df <-  data.frame(dates = as.yearmon("2018-08") + 0:6/12, values = c(2:6, 0, 1))
ggdf <- ggplot(df, aes(x = dates, y = values)) +
  geom_bar(position = "dodge", stat = "identity") + theme_light() +
  xlab("Month") + ylab("Values")
ggdf ## with default scale_x_yearmon
ggdf + scale_x_yearmon(breaks = df$dates) ## with custom discrete breaks
}

[Package zoo version 1.8-12 Index]