lightweightchartR

lightweightchartR brings TradingView's lightweight-charts library to R in a package designed for quantmod users.

The goal is simple:

• make interactive market charts feel natural in R
• keep the workflow pipe-friendly
• support common trading-chart patterns like volume overlays, moving averages, and indicator panes without a lot of setup

Why this package?

If you already work with quantmod, xts, and pipe-based workflows, this package gives you a more modern interactive charting layer while keeping the data pipeline familiar.

Instead of building chart specs by hand, you can do this:

library(quantmod)
library(lightweightchartR)

getSymbols("SPY", from = "2024-01-01")

SPY |>
  lwc_chart(theme = "dark", name = "SPY") |>
  add_volume() |>
  add_sma(50, color = "blue") |>
  add_sma(200, color = "goldenrod") |>
  add_rsi()

Features

• TradingView lightweight-charts powered htmlwidget
• Pipe-first API
• Works naturally with xts, zoo, and quantmod
• Candles, bars, lines, areas, and histograms
• Volume overlays in the main price pane
• Technical indicators like SMA, EMA, BBands, RSI, and MACD
• Multi-pane charts
• Hover tooltips for technical overlays in the price pane
• Shiny support
• A small compatibility bridge for chartSeries()-style workflows

Example

library(quantmod)
library(lightweightchartR)

getSymbols("AAPL", from = "2023-01-01")

AAPL |>
  lwc_chart(theme = "dark", name = "AAPL") |>
  add_volume() |>
  add_sma(20, color = "#2563eb") |>
  add_sma(50, color = "#f59e0b")

Quantmod-style bridge

For users migrating from quantmod::chartSeries(), there is also a compact wrapper:

chart_series_lwc(
  AAPL,
  theme = "dark",
  TA = "addVo();addSMA(n = 20);addRSI()"
)

Installation

Install from GitHub once the repository is published:

# pak::pak("arkraieski/lightweightchartR")
install.packages("lightweightchartR", repos = c('https://arkraieski.r-universe.dev', 'https://cloud.r-project.org'))

Status

The package is currently focused on:

• quantmod workflows
• clean defaults for market-chart use cases
• a small, practical API rather than exposing every charting knob up front

More advanced customization can be added over time where it clearly improves real workflows.