--- title: "Getting Started" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{Getting Started} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r, include = FALSE} knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ``` `lightweightchartR` brings TradingView's `lightweight-charts` library to R with an API that feels natural for `quantmod` and `xts` users. The package is built around a simple idea: - start with market data - create a chart with `lwc_chart()` - add layers and indicators with pipes ## Load packages ```{r} library(quantmod) library(lightweightchartR) ``` ## Download some market data We'll use Apple price data from Yahoo Finance. ```{r} getSymbols("AAPL", from = "2024-01-01", auto.assign = TRUE) aapl <- AAPL head(aapl) ``` ## Create a basic chart If your data has OHLC columns, `lwc_chart()` will automatically choose a candlestick chart. ```{r} aapl |> lwc_chart(theme = "dark", name = "AAPL") ``` ## Add volume and moving averages You can layer additional series with a pipe-first workflow. ```{r} aapl |> lwc_chart(theme = "dark", name = "AAPL") |> add_volume() |> add_sma(20, color = "#2563eb") |> add_sma(50, color = "#f59e0b") ``` By default: - volume overlays into the main price pane - moving averages added with `add_sma()` are drawn in the price pane ## Add an indicator pane Indicators like RSI can go into their own pane. ```{r} aapl |> lwc_chart(theme = "dark", name = "AAPL") |> add_volume() |> add_sma(20, color = "#2563eb") |> add_sma(50, color = "#f59e0b") |> add_rsi() ``` ## Use the quantmod-style bridge If you're coming from `chartSeries()`, the package also includes a compact compatibility wrapper. ```{r} chart_series_lwc( aapl, theme = "dark", TA = "addVo();addSMA(n = 20);addRSI()" ) ``` ## Customize chart-level behavior `lwc_chart()` also lets you control chart-wide behavior such as widget height and technical-analysis hover tooltips. ```{r} aapl |> lwc_chart( theme = "dark", name = "AAPL", height = 260, ta_tooltip = TRUE, ta_tooltip_threshold = 10 ) |> add_volume() |> add_sma(20, color = "#2563eb") |> add_sma(50, color = "#f59e0b") ``` ## Summary The basic workflow is: 1. Start with `xts` market data 2. Call `lwc_chart()` 3. Add layers and indicators with `add_*()` helpers That gives you a modern interactive chart while keeping the workflow familiar for `quantmod` users.