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plot_candlestick

function backtide.analysis.candlestick.plot_candlestick(data, rangeslider=True, title=None, legend="upper left", figsize=(900, 600), filename=None, display=True)[source]

Create a candlestick chart.

Visualizes OHLC (Open-High-Low-Close) price data over time as candlestick bars — the standard chart type used in financial technical analysis. When the dataframe contains multiple symbols, each symbol gets its own color-coded candlestick trace with a matching close-price line overlay for readability.

Parameters

data : pd.DataFrame | pl.DataFrame

Input data containing columns open, high, low, close and dt with the datetime.

rangeslider : bool, default=True
Whether to show the range slider below the chart.

title : str | dict | None, default=None
Title for the plot.

legend : str | dict | None, default="upper left"
Legend for the plot. See the user guide for an extended description of the choices.

  • If None: No legend is shown.
  • If str: Position to display the legend.
  • If dict: Legend configuration.

figsize : tuple[int, int], default=(900, 600)
Figure's size in pixels, format as (x, y).

filename : str | Path | None, default=None
Save the plot using this name. The type of the file depends on the provided name (.html, .png, .pdf, etc...). If filename has no file type, the plot is saved as .html. If None, the plot isn't saved.

display : bool | None, default=True
Whether to render the plot. If None, it returns the figure.
Returns

Figure | None

The Plotly figure object. Only returned if display=None.


See Also

plot_price

Create a price line chart.

plot_volume

Create a trading volume bar chart.

plot_vwap

Create a VWAP (Volume-Weighted Average Price) chart.


Example

>>> from backtide.storage import query_bars
>>> from backtide.analysis import plot_candlestick

>>> df = query_bars("AAPL", "1d")

>>> # Show only the last 30 days
>>> df = df.sort_values("open_ts").iloc[-30:]

>>> plot_candlestick(df, title="AAPL Daily")