The highcharter package include highstocks libraries from highchartsJS to create stock or general timeline charts. Features sophisticated navigation for high-volume data, user annotations and range selectors.
Basics
Highstock work well with the quantmod package. It’s easy chart
symbols using hchart()
. Then you can add more series using
hc_add_series()
.
library(quantmod)
x <- getSymbols("GOOG", auto.assign = FALSE)
hchart(x)
Obviously you can use the implemented API functions to edit the chart:
y <- getSymbols("AMZN", auto.assign = FALSE)
hchart(y, type = "ohlc") |>
hc_title(text = "This is a Open-high-low-close chart with a custom theme") |>
hc_add_theme(hc_theme_db())
Candlestick and OHLC charts
If you want to chart more symbols in you can use the
hc_add_series()
function. Don’t forget to specify
type = "stock"
to activate the navigator, range selector
and other features of highstock.
hc <- highchart(type = "stock") |>
hc_add_series(x, id = 1) |>
hc_add_series(y, type = "ohlc", id = 2)
hc
Flags
Previously we used the id
parameter. This is necessary
to add flags to relate series and flags:
library(dplyr)
set.seed(123)
data_flags <- tibble(
date = sample(time(x), size = 5),
title = sprintf("E #%s", seq_along(date)),
text = sprintf("An interesting event #%s in %s", seq_along(date), date)
)
glimpse(data_flags)
## Rows: 5
## Columns: 3
## $ date <date> 2016-10-12, 2016-12-20, 2015-11-04, 2009-02-03, 2007-10-10
## $ title <chr> "E #1", "E #2", "E #3", "E #4", "E #5"
## $ text <chr> "An interesting event #1 in 2016-10-12", "An interesting event …
hc |>
hc_add_series(
data_flags,
hcaes(x = date),
type = "flags",
onSeries = 2
)