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https://github.com/OpenBB-finance/OpenBB.git
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13283fbfce
* BIGGGG LINTING * fixing lints * fixing lints * black * very ruff * no export * fix hedge_view again * lints * platform lints * lints * black * black it @hjoaquim * fix some more linting --------- Co-authored-by: hjoaquim <h.joaquim@campus.fct.unl.pt>
465 lines
11 KiB
Python
465 lines
11 KiB
Python
"""Rolling Statistics View"""
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__docformat__ = "numpy"
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import logging
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import os
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from typing import Optional, Union
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import pandas as pd
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from openbb_terminal import OpenBBFigure
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from openbb_terminal.common.quantitative_analysis import rolling_model
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from openbb_terminal.decorators import log_start_end
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from openbb_terminal.helper_funcs import export_data
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logger = logging.getLogger(__name__)
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@log_start_end(log=logger)
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def display_mean_std(
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data: pd.DataFrame,
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target: str,
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symbol: str = "",
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window: int = 14,
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export: str = "",
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sheet_name: Optional[str] = None,
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external_axes: bool = False,
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) -> Union[OpenBBFigure, None]:
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"""Plots mean std deviation
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Parameters
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----------
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data: pd.DataFrame
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Dataframe
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target: str
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Column in data to look at
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symbol : str
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Stock ticker
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window : int
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Length of window
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sheet_name: str
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Optionally specify the name of the sheet the data is exported to.
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export: str
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Format to export data
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external_axes : bool, optional
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Whether to return the figure object or not, by default False
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"""
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data = data[target]
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rolling_mean, rolling_std = rolling_model.get_rolling_avg(data, window)
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plot_data = pd.merge(
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data,
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rolling_mean,
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how="outer",
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left_index=True,
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right_index=True,
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suffixes=("", "_mean"),
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)
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plot_data = pd.merge(
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plot_data,
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rolling_std,
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how="outer",
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left_index=True,
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right_index=True,
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suffixes=("", "_std"),
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)
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fig = OpenBBFigure.create_subplots(
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2,
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1,
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shared_xaxes=True,
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subplot_titles=[
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f"Rolling mean and std (window {str(window)}) of {symbol} {target}"
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],
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vertical_spacing=0.1,
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)
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fig.add_scatter(
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x=plot_data.index,
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y=plot_data[target].values,
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name="Real Values",
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legend="legend",
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row=1,
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col=1,
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)
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fig.add_scatter(
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x=plot_data.index,
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y=plot_data[target + "_mean"].values,
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name="Rolling Mean",
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legend="legend",
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row=1,
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col=1,
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)
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fig.add_scatter(
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x=plot_data.index,
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y=plot_data[target + "_std"].values,
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name="Rolling Std",
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legend="legend2",
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row=2,
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col=1,
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)
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fig.update_layout(
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legend=dict(xref="paper", yref="paper"),
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legend2=dict(
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xanchor="left",
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yanchor="top",
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xref="paper",
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yref="paper",
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x=0.01,
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y=0.44,
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),
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yaxis=dict(title="Values"),
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yaxis2=dict(title=f"{target} Std Deviation"),
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)
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export_data(
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export,
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os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
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"rolling",
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rolling_mean.join(rolling_std, lsuffix="_mean", rsuffix="_std"),
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sheet_name,
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fig,
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)
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return fig.show(external=external_axes)
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@log_start_end(log=logger)
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def display_spread(
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data: pd.DataFrame,
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target: str,
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symbol: str = "",
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window: int = 14,
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export: str = "",
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sheet_name: Optional[str] = None,
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external_axes: bool = False,
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) -> Union[OpenBBFigure, None]:
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"""Plots rolling spread
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Parameters
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----------
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data: pd.DataFrame
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Dataframe
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target: str
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Column in data to look at
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target: str
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Column in data to look at
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symbol : str
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Stock ticker
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window : int
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Length of window
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sheet_name: str
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Optionally specify the name of the sheet the data is exported to.
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export: str
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Format to export data
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external_axes : bool, optional
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Whether to return the figure object or not, by default False
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"""
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data = data[target]
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df_sd, df_var = rolling_model.get_spread(data, window)
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plot_data = pd.merge(
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data,
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df_sd,
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how="outer",
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left_index=True,
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right_index=True,
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suffixes=("", "_sd"),
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)
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plot_data = pd.merge(
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plot_data,
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df_var,
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how="outer",
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left_index=True,
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right_index=True,
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suffixes=("", "_var"),
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)
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fig = OpenBBFigure.create_subplots(
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3,
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1,
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shared_xaxes=True,
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subplot_titles=[
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"Real Values",
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"Rolling Stdev",
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"Rolling Variance",
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],
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vertical_spacing=0.1,
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).set_title(f"Spread of {symbol} {target}")
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fig.add_scatter(
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x=plot_data.index,
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y=plot_data[target].values,
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name="Real Values",
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row=1,
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col=1,
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)
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fig.add_scatter(
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x=plot_data.index,
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y=plot_data[f"STDEV_{window}"].values,
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name="Rolling Stdev",
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row=2,
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col=1,
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)
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fig.add_scatter(
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x=plot_data.index,
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y=plot_data[f"VAR_{window}"].values,
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name="Rolling Variance",
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row=3,
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col=1,
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)
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fig.update_layout(
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yaxis=dict(title="Values"),
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yaxis2=dict(title="Stdev"),
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yaxis3=dict(title="Variance"),
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)
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fig.update_traces(showlegend=False)
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export_data(
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export,
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os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
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"spread",
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df_sd.join(df_var, lsuffix="_sd", rsuffix="_var"),
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sheet_name,
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fig,
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)
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return fig.show(external=external_axes)
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@log_start_end(log=logger)
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def display_quantile(
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data: pd.DataFrame,
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target: str,
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symbol: str = "",
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window: int = 14,
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quantile: float = 0.5,
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export: str = "",
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sheet_name: Optional[str] = None,
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external_axes: bool = False,
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) -> Union[OpenBBFigure, None]:
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"""Plots rolling quantile
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Parameters
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----------
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data: pd.DataFrame
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Dataframe
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target: str
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Column in data to look at
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symbol : str
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Stock ticker
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window : int
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Length of window
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quantile: float
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Quantile to get
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sheet_name: str
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Optionally specify the name of the sheet the data is exported to.
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export: str
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Format to export data
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external_axes: bool, optional
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Whether to return the figure object or not, by default False
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"""
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data = data[target]
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df_med, df_quantile = rolling_model.get_quantile(data, window, quantile)
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plot_data = pd.merge(
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data,
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df_med,
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how="outer",
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left_index=True,
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right_index=True,
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suffixes=("", "_med"),
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)
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plot_data = pd.merge(
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plot_data,
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df_quantile,
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how="outer",
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left_index=True,
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right_index=True,
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suffixes=("", "_quantile"),
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)
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fig = OpenBBFigure().set_title(f"{symbol} {target} Median & Quantile")
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fig.add_scatter(
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x=plot_data.index,
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y=plot_data[target].values,
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name=target,
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)
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fig.add_scatter(
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x=plot_data.index,
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y=plot_data[f"MEDIAN_{window}"].values,
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name=f"Median w={window}",
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)
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fig.add_scatter(
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x=plot_data.index,
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y=plot_data[f"QTL_{window}_{quantile}"].values,
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name=f"Quantile q={quantile}",
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line=dict(dash="dash"),
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)
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fig.update_layout(yaxis=dict(title=f"{symbol} Value"))
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export_data(
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export,
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os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
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"quantile",
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df_med.join(df_quantile),
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sheet_name,
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fig,
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)
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return fig.show(external=external_axes)
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@log_start_end(log=logger)
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def display_skew(
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symbol: str,
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data: pd.DataFrame,
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target: str,
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window: int = 14,
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export: str = "",
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sheet_name: Optional[str] = None,
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external_axes: bool = False,
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) -> Union[OpenBBFigure, None]:
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"""Plots rolling skew
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Parameters
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----------
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symbol: str
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Stock ticker
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data: pd.DataFrame
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Dataframe
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target: str
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Column in data to look at
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window: int
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Length of window
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sheet_name: str
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Optionally specify the name of the sheet the data is exported to.
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export: str
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Format to export data
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external_axes : bool, optional
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Whether to return the figure object or not, by default False
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"""
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data = data[target]
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df_skew = rolling_model.get_skew(data, window)
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plot_data = pd.merge(
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data,
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df_skew,
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how="outer",
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left_index=True,
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right_index=True,
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)
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fig = OpenBBFigure.create_subplots(
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rows=2,
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cols=1,
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vertical_spacing=0.1,
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).set_title(f"{symbol} Skewness Indicator")
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fig.add_scatter(
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x=plot_data.index,
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y=plot_data[target].values,
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name=target,
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row=1,
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col=1,
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)
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fig.add_scatter(
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x=plot_data.index,
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y=plot_data[f"SKEW_{window}"].values,
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name=f"Skew w={window}",
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row=2,
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col=1,
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)
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fig.update_layout(yaxis=dict(title=f"{target}"), yaxis2=dict(title="Indicator"))
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export_data(
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export,
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os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
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"skew",
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df_skew,
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sheet_name,
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fig,
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)
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return fig.show(external=external_axes)
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@log_start_end(log=logger)
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def display_kurtosis(
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symbol: str,
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data: pd.DataFrame,
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target: str,
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window: int = 14,
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export: str = "",
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sheet_name: Optional[str] = None,
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external_axes: bool = False,
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) -> Union[OpenBBFigure, None]:
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"""Plots rolling kurtosis
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Parameters
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----------
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symbol: str
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Ticker
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data: pd.DataFrame
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Dataframe of stock prices
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target: str
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Column in data to look at
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window: int
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Length of window
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sheet_name: str
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Optionally specify the name of the sheet the data is exported to.
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export: str
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Format to export data
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external_axes : bool, optional
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Whether to return the figure object or not, by default False
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"""
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data = data[target]
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df_kurt = rolling_model.get_kurtosis(data, window)
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plot_data = pd.merge(
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data,
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df_kurt,
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how="outer",
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left_index=True,
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right_index=True,
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)
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fig = OpenBBFigure.create_subplots(
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rows=2,
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cols=1,
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vertical_spacing=0.1,
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subplot_titles=[f"{target}", "Kurtosis"],
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).set_title(f"{symbol} {target} Kurtosis Indicator (window {str(window)})")
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fig.add_scatter(
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x=plot_data.index,
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y=plot_data[target].values,
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name=target,
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row=1,
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col=1,
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)
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fig.add_scatter(
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x=plot_data.index,
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y=plot_data[f"KURT_{window}"].values,
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name=f"Kurtosis w={window}",
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row=2,
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col=1,
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)
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fig.update_layout(yaxis=dict(title=f"{target}"), yaxis2=dict(title="Indicator"))
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fig.update_traces(showlegend=False)
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export_data(
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export,
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os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
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"kurtosis",
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df_kurt,
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sheet_name,
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fig,
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)
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return fig.show(external=external_axes)
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