Candlestick Charts in R

How to create candlestick charts in R.


New to Plotly?

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')
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## [1] "AAPL"
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# 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
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Basic Candlestick ChartDate

Candlestick without Rangeslider

library(plotly)
library(quantmod)

getSymbols("AAPL",src='yahoo')
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## [1] "AAPL"
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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
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Apr 212024Apr 28May 5May 12May 19May 26165170175180185190
Basic Candlestick ChartDate

Customise the fig ure with Shapes and Annotations

library(plotly)
library(quantmod)

getSymbols("AAPL",src='yahoo')
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## [1] "AAPL"
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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
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Custom Candlestick Colors

library(plotly)
library(quantmod)

getSymbols("AAPL",src='yahoo')
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## [1] "AAPL"
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# 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
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Apr 212024Apr 28May 5May 12May 19May 26165170175180185190
Date

Add a Trace to Candlestick Chart

library(plotly)
library(quantmod)

getSymbols("AAPL",src='yahoo')
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## [1] "AAPL"
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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
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AAPL.OpenDate

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
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Pricedate

Add Bollinger Bands and Buttons

library(plotly)
library(quantmod)

# get data
getSymbols("AAPL",src='yahoo')
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## [1] "AAPL"
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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
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AAPLB BandsMv AvgAAPL VolumeAAPL VolumeRESET1 YR3 MO1 MOApple: 2015-02-14 - 2024-05-29PriceVolumeDate

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)
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