R: Plot Financial Charts in ggplot2

geom_chart {tidyquant} | R Documentation

## 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:

- Bar Chart

- Candlestick Chart

### 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, as a string.
`position` | Position adjustment, either as a string, or the result of a call to a position adjustment function.
`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 behaviour 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

    # Load libraries
    library(tidyquant)
    library(dplyr)
    library(ggplot2)

    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(75, 125))

    # 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(75, 125))

[Package tidyquant version 1.0.0 Index]