Candlestick Charts in R
How to create candlestick charts in R.
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Plotly is a free and open-source graphing library for R. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.
Basic Candlestick
library(plotly)
library(quantmod)
getSymbols("AAPL",src='yahoo')
## [1] "AAPL"
# basic example of ohlc charts
df <- data.frame(Date=index(AAPL),coredata(AAPL))
df <- tail(df, 30)
fig <- df %>% plot_ly(x = ~Date, type="candlestick",
open = ~AAPL.Open, close = ~AAPL.Close,
high = ~AAPL.High, low = ~AAPL.Low)
fig <- fig %>% layout(title = "Basic Candlestick Chart")
fig
Candlestick without Rangeslider
library(plotly)
library(quantmod)
getSymbols("AAPL",src='yahoo')
## [1] "AAPL"
df <- data.frame(Date=index(AAPL),coredata(AAPL))
df <- tail(df, 30)
fig <- df %>% plot_ly(x = ~Date, type="candlestick",
open = ~AAPL.Open, close = ~AAPL.Close,
high = ~AAPL.High, low = ~AAPL.Low)
fig <- fig %>% layout(title = "Basic Candlestick Chart",
xaxis = list(rangeslider = list(visible = F)))
fig
Customise the fig ure with Shapes and Annotations
library(plotly)
library(quantmod)
getSymbols("AAPL",src='yahoo')
## [1] "AAPL"
df <- data.frame(Date=index(AAPL),coredata(AAPL))
# annotation
a <- list(text = "Stock Split",
x = '2014-06-06',
y = 1.02,
xref = 'x',
yref = 'paper',
xanchor = 'left',
showarrow = FALSE
)
# use shapes to create a line
l <- list(type = line,
x0 = '2014-06-06',
x1 = '2014-06-06',
y0 = 0,
y1 = 1,
xref = 'x',
yref = 'paper',
line = list(color = 'black',
width = 0.5)
)
fig <- df %>% plot_ly(x = ~Date, type="candlestick",
open = ~AAPL.Open, close = ~AAPL.Close,
high = ~AAPL.High, low = ~AAPL.Low)
fig <- fig %>% layout(title = "Apple Stock",
annotations = a,
shapes = l)
fig
Custom Candlestick Colors
library(plotly)
library(quantmod)
getSymbols("AAPL",src='yahoo')
## [1] "AAPL"
# basic example of ohlc charts
df <- data.frame(Date=index(AAPL),coredata(AAPL))
df <- tail(df, 30)
# cutom colors
i <- list(line = list(color = '#FFD700'))
d <- list(line = list(color = '#0000ff'))
fig <- df %>% plot_ly(x = ~Date, type="candlestick",
open = ~AAPL.Open, close = ~AAPL.Close,
high = ~AAPL.High, low = ~AAPL.Low,
increasing = i, decreasing = d)
fig
Add a Trace to Candlestick Chart
library(plotly)
library(quantmod)
getSymbols("AAPL",src='yahoo')
## [1] "AAPL"
df <- data.frame(Date=index(AAPL),coredata(AAPL))
df <- tail(df, 365)
fig <- df %>% plot_ly(x = ~Date, type="candlestick",
open = ~AAPL.Open, close = ~AAPL.Close,
high = ~AAPL.High, low = ~AAPL.Low)
fig <- fig %>% add_lines(x = ~Date, y = ~AAPL.Open, line = list(color = 'black', width = 0.75), inherit = F)
fig <- fig %>% layout(showlegend = FALSE)
fig
Candlestick Using Segments
library(plotly)
library(quantmod)
msft <- getSymbols("MSFT", auto.assign = F)
dat <- as.data.frame(msft)
dat$date <- index(msft)
dat <- subset(dat, date >= "2016-01-01")
names(dat) <- sub("^MSFT\\.", "", names(dat))
fig <- plot_ly(dat, x = ~date, xend = ~date, color = ~Close > Open,
colors = c("red", "forestgreen"), hoverinfo = "none")
fig <- fig %>% add_segments(y = ~Low, yend = ~High, size = I(1))
fig <- fig %>% add_segments(y = ~Open, yend = ~Close, size = I(3))
fig <- fig %>% layout(showlegend = FALSE, yaxis = list(title = "Price"))
fig <- fig %>% rangeslider()
fig
Add Bollinger Bands and Buttons
library(plotly)
library(quantmod)
# get data
getSymbols("AAPL",src='yahoo')
## [1] "AAPL"
df <- data.frame(Date=index(AAPL),coredata(AAPL))
# create Bollinger Bands
bbands <- BBands(AAPL[,c("AAPL.High","AAPL.Low","AAPL.Close")])
# join and subset data
df <- subset(cbind(df, data.frame(bbands[,1:3])), Date >= "2015-02-14")
# colors column for increasing and decreasing
for (i in 1:length(df[,1])) {
if (df$AAPL.Close[i] >= df$AAPL.Open[i]) {
df$direction[i] = 'Increasing'
} else {
df$direction[i] = 'Decreasing'
}
}
i <- list(line = list(color = '#17BECF'))
d <- list(line = list(color = '#7F7F7F'))
# plot candlestick chart
fig <- df %>% plot_ly(x = ~Date, type="candlestick",
open = ~AAPL.Open, close = ~AAPL.Close,
high = ~AAPL.High, low = ~AAPL.Low, name = "AAPL",
increasing = i, decreasing = d)
fig <- fig %>% add_lines(x = ~Date, y = ~up , name = "B Bands",
line = list(color = '#ccc', width = 0.5),
legendgroup = "Bollinger Bands",
hoverinfo = "none", inherit = F)
fig <- fig %>% add_lines(x = ~Date, y = ~dn, name = "B Bands",
line = list(color = '#ccc', width = 0.5),
legendgroup = "Bollinger Bands", inherit = F,
showlegend = FALSE, hoverinfo = "none")
fig <- fig %>% add_lines(x = ~Date, y = ~mavg, name = "Mv Avg",
line = list(color = '#E377C2', width = 0.5),
hoverinfo = "none", inherit = F)
fig <- fig %>% layout(yaxis = list(title = "Price"))
# plot volume bar chart
fig2 <- df
fig2 <- fig2 %>% plot_ly(x=~Date, y=~AAPL.Volume, type='bar', name = "AAPL Volume",
color = ~direction, colors = c('#17BECF','#7F7F7F'))
fig2 <- fig2 %>% layout(yaxis = list(title = "Volume"))
# create rangeselector buttons
rs <- list(visible = TRUE, x = 0.5, y = -0.055,
xanchor = 'center', yref = 'paper',
font = list(size = 9),
buttons = list(
list(count=1,
label='RESET',
step='all'),
list(count=1,
label='1 YR',
step='year',
stepmode='backward'),
list(count=3,
label='3 MO',
step='month',
stepmode='backward'),
list(count=1,
label='1 MO',
step='month',
stepmode='backward')
))
# subplot with shared x axis
fig <- subplot(fig, fig2, heights = c(0.7,0.2), nrows=2,
shareX = TRUE, titleY = TRUE)
fig <- fig %>% layout(title = paste("Apple: 2015-02-14 -",Sys.Date()),
xaxis = list(rangeselector = rs),
legend = list(orientation = 'h', x = 0.5, y = 1,
xanchor = 'center', yref = 'paper',
font = list(size = 10),
bgcolor = 'transparent'))
fig
Reference
See https://plotly.com/r/reference for more information and chart attribute options!
What About Dash?
Dash for R is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.
Learn about how to install Dash for R at https://dashr.plot.ly/installation.
Everywhere in this page that you see fig
, you can display the same figure in a Dash for R application by passing it to the figure
argument of the Graph
component from the built-in dashCoreComponents
package like this:
library(plotly)
fig <- plot_ly()
# fig <- fig %>% add_trace( ... )
# fig <- fig %>% layout( ... )
library(dash)
library(dashCoreComponents)
library(dashHtmlComponents)
app <- Dash$new()
app$layout(
htmlDiv(
list(
dccGraph(figure=fig)
)
)
)
app$run_server(debug=TRUE, dev_tools_hot_reload=FALSE)