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tidyquant (version 1.0.9)

geom_chart: Plot Financial Charts in ggplot2

Description

Financial charts provide visual cues to open, high, low, and close prices. Use coord_x_date() to zoom into specific plot regions. The following financial chart geoms are available:

Usage

geom_barchart(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  na.rm = TRUE,
  show.legend = NA,
  inherit.aes = TRUE,
  colour_up = "darkblue",
  colour_down = "red",
  fill_up = "darkblue",
  fill_down = "red",
  ...
)

geom_candlestick( mapping = NULL, data = NULL, stat = "identity", position = "identity", na.rm = TRUE, show.legend = NA, inherit.aes = TRUE, colour_up = "darkblue", colour_down = "red", fill_up = "darkblue", fill_down = "red", ... )

Arguments

mapping

Set of aesthetic mappings created by ggplot2::aes() or ggplot2::aes_(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot2::ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See ggplot2::fortify() for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame., and will be used as the layer data.

stat

The statistical transformation to use on the data for this layer. When using a geom_*() function to construct a layer, the stat argument can be used the override the default coupling between geoms and stats. The stat argument accepts the following:

  • A Stat ggproto subclass, for example StatCount.

  • A string naming the stat. To give the stat as a string, strip the function name of the stat_ prefix. For example, to use stat_count(), give the stat as "count".

  • For more information and other ways to specify the stat, see the layer stat documentation.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

  • The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.

  • A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".

  • For more information and other ways to specify the position, see the layer position documentation.

na.rm

If TRUE, silently removes NA values, which typically desired for moving averages.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behavior from the default plot specification, e.g. ggplot2::borders().

colour_up, colour_down

Select colors to be applied based on price movement from open to close. If close >= open, colour_up is used. Otherwise, colour_down is used. The default is "darkblue" and "red", respectively.

fill_up, fill_down

Select fills to be applied based on price movement from open to close. If close >= open, fill_up is used. Otherwise, fill_down is used. The default is "darkblue" and "red", respectively. Only affects geom_candlestick().

...

Other arguments passed on to ggplot2::layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like color = "red" or size = 3. They may also be parameters to the paired geom/stat.

Aesthetics

The following aesthetics are understood (required are in bold):

  • x, Typically a date

  • open, Required to be the open price

  • high, Required to be the high price

  • low, Required to be the low price

  • close, Required to be the close price

  • alpha

  • group

  • linetype

  • size

See Also

See individual modeling functions for underlying parameters:

  • geom_ma() for adding moving averages to ggplots

  • geom_bbands() for adding Bollinger Bands to ggplots

  • coord_x_date() for zooming into specific regions of a plot

Examples

Run this code
library(dplyr)
library(ggplot2)
library(lubridate)

AAPL <- tq_get("AAPL", from = "2013-01-01", to = "2016-12-31")

# Bar Chart
AAPL %>%
    ggplot(aes(x = date, y = close)) +
    geom_barchart(aes(open = open, high = high, low = low, close = close)) +
    geom_ma(color = "darkgreen") +
    coord_x_date(xlim = c("2016-01-01", "2016-12-31"),
                 ylim = c(20, 30))

# Candlestick Chart
AAPL %>%
    ggplot(aes(x = date, y = close)) +
    geom_candlestick(aes(open = open, high = high, low = low, close = close)) +
    geom_ma(color = "darkgreen") +
    coord_x_date(xlim = c("2016-01-01", "2016-12-31"),
                 ylim = c(20, 30))

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