plot_volume

---

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

Create a trading volume bar chart.

Displays trading volume over time for one or more symbols. Each symbol is rendered as a separate bar trace.

Parameters

data : pd.DataFrame | pl.DataFrame Input data containing columns symbol, volume and dt with the datetime. title : str | dict | None, default=None Title for the plot. If None, no title is shown. If str, text for the title. If dict, title configuration. 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_candlestick

Create a candlestick chart.

plot_price

Create a price line chart.

plot_vwap

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

Example

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

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

>>> # Plot raw share volume
>>> plot_volume(df)

>>> # Plot price x share (dollar volume)
>>> df_vol = df.copy()
>>> df_vol["volume"] = df_vol["volume"] * df_vol["close"]
>>> df_vol["currency"] = "USD"  # Add currency to format labels
>>> plot_volume(df_vol, title="Dollar volume for Apple")