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-rw-r--r--openbb_terminal/common/quantitative_analysis/rolling_view.py464
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diff --git a/openbb_terminal/common/quantitative_analysis/rolling_view.py b/openbb_terminal/common/quantitative_analysis/rolling_view.py
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--- a/openbb_terminal/common/quantitative_analysis/rolling_view.py
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-"""Rolling Statistics View"""
-
-__docformat__ = "numpy"
-
-import logging
-import os
-from typing import Optional, Union
-
-import pandas as pd
-
-from openbb_terminal import OpenBBFigure
-from openbb_terminal.common.quantitative_analysis import rolling_model
-from openbb_terminal.decorators import log_start_end
-from openbb_terminal.helper_funcs import export_data
-
-logger = logging.getLogger(__name__)
-
-
-@log_start_end(log=logger)
-def display_mean_std(
- data: pd.DataFrame,
- target: str,
- symbol: str = "",
- window: int = 14,
- export: str = "",
- sheet_name: Optional[str] = None,
- external_axes: bool = False,
-) -> Union[OpenBBFigure, None]:
- """Plots mean std deviation
-
- Parameters
- ----------
- data: pd.DataFrame
- Dataframe
- target: str
- Column in data to look at
- symbol : str
- Stock ticker
- window : int
- Length of window
- sheet_name: str
- Optionally specify the name of the sheet the data is exported to.
- export: str
- Format to export data
- external_axes : bool, optional
- Whether to return the figure object or not, by default False
- """
- data = data[target]
- rolling_mean, rolling_std = rolling_model.get_rolling_avg(data, window)
- plot_data = pd.merge(
- data,
- rolling_mean,
- how="outer",
- left_index=True,
- right_index=True,
- suffixes=("", "_mean"),
- )
- plot_data = pd.merge(
- plot_data,
- rolling_std,
- how="outer",
- left_index=True,
- right_index=True,
- suffixes=("", "_std"),
- )
-
- fig = OpenBBFigure.create_subplots(
- 2,
- 1,
- shared_xaxes=True,
- subplot_titles=[
- f"Rolling mean and std (window {str(window)}) of {symbol} {target}"
- ],
- vertical_spacing=0.1,
- )
- fig.add_scatter(
- x=plot_data.index,
- y=plot_data[target].values,
- name="Real Values",
- legend="legend",
- row=1,
- col=1,
- )
- fig.add_scatter(
- x=plot_data.index,
- y=plot_data[target + "_mean"].values,
- name="Rolling Mean",
- legend="legend",
- row=1,
- col=1,
- )
- fig.add_scatter(
- x=plot_data.index,
- y=plot_data[target + "_std"].values,
- name="Rolling Std",
- legend="legend2",
- row=2,
- col=1,
- )
- fig.update_layout(
- legend=dict(xref="paper", yref="paper"),
- legend2=dict(
- xanchor="left",
- yanchor="top",
- xref="paper",
- yref="paper",
- x=0.01,
- y=0.44,
- ),
- yaxis=dict(title="Values"),
- yaxis2=dict(title=f"{target} Std Deviation"),
- )
-
- export_data(
- export,
- os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
- "rolling",
- rolling_mean.join(rolling_std, lsuffix="_mean", rsuffix="_std"),
- sheet_name,
- fig,
- )
-
- return fig.show(external=external_axes)
-
-
-@log_start_end(log=logger)
-def display_spread(
- data: pd.DataFrame,
- target: str,
- symbol: str = "",
- window: int = 14,
- export: str = "",
- sheet_name: Optional[str] = None,
- external_axes: bool = False,
-) -> Union[OpenBBFigure, None]:
- """Plots rolling spread
-
- Parameters
- ----------
- data: pd.DataFrame
- Dataframe
- target: str
- Column in data to look at
- target: str
- Column in data to look at
- symbol : str
- Stock ticker
- window : int
- Length of window
- sheet_name: str
- Optionally specify the name of the sheet the data is exported to.
- export: str
- Format to export data
- external_axes : bool, optional
- Whether to return the figure object or not, by default False
- """
- data = data[target]
- df_sd, df_var = rolling_model.get_spread(data, window)
-
- plot_data = pd.merge(
- data,
- df_sd,
- how="outer",
- left_index=True,
- right_index=True,
- suffixes=("", "_sd"),
- )
- plot_data = pd.merge(
- plot_data,
- df_var,
- how="outer",
- left_index=True,
- right_index=True,
- suffixes=("", "_var"),
- )
-
- fig = OpenBBFigure.create_subplots(
- 3,
- 1,
- shared_xaxes=True,
- subplot_titles=[
- "Real Values",
- "Rolling Stdev",
- "Rolling Variance",
- ],
- vertical_spacing=0.1,
- ).set_title(f"Spread of {symbol} {target}")
-
- fig.add_scatter(
- x=plot_data.index,
- y=plot_data[target].values,
- name="Real Values",
- row=1,
- col=1,
- )
- fig.add_scatter(
- x=plot_data.index,
- y=plot_data[f"STDEV_{window}"].values,
- name="Rolling Stdev",
- row=2,
- col=1,
- )
- fig.add_scatter(
- x=plot_data.index,
- y=plot_data[f"VAR_{window}"].values,
- name="Rolling Variance",
- row=3,
- col=1,
- )
- fig.update_layout(
- yaxis=dict(title="Values"),
- yaxis2=dict(title="Stdev"),
- yaxis3=dict(title="Variance"),
- )
- fig.update_traces(showlegend=False)
-
- export_data(
- export,
- os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
- "spread",
- df_sd.join(df_var, lsuffix="_sd", rsuffix="_var"),
- sheet_name,
- fig,
- )
-
- return fig.show(external=external_axes)
-
-
-@log_start_end(log=logger)
-def display_quantile(
- data: pd.DataFrame,
- target: str,
- symbol: str = "",
- window: int = 14,
- quantile: float = 0.5,
- export: str = "",
- sheet_name: Optional[str] = None,
- external_axes: bool = False,
-) -> Union[OpenBBFigure, None]:
- """Plots rolling quantile
-
- Parameters
- ----------
- data: pd.DataFrame
- Dataframe
- target: str
- Column in data to look at
- symbol : str
- Stock ticker
- window : int
- Length of window
- quantile: float
- Quantile to get
- sheet_name: str
- Optionally specify the name of the sheet the data is exported to.
- export: str
- Format to export data
- external_axes: bool, optional
- Whether to return the figure object or not, by default False
- """
- data = data[target]
- df_med, df_quantile = rolling_model.get_quantile(data, window, quantile)
-
- plot_data = pd.merge(
- data,
- df_med,
- how="outer",
- left_index=True,
- right_index=True,
- suffixes=("", "_med"),
- )
- plot_data = pd.merge(
- plot_data,
- df_quantile,
- how="outer",
- left_index=True,
- right_index=True,
- suffixes=("", "_quantile"),
- )
-
- fig = OpenBBFigure().set_title(f"{symbol} {target} Median & Quantile")
-
- fig.add_scatter(
- x=plot_data.index,
- y=plot_data[target].values,
- name=target,
- )
- fig.add_scatter(
- x=plot_data.index,
- y=plot_data[f"MEDIAN_{window}"].values,
- name=f"Median w={window}",
- )
- fig.add_scatter(
- x=plot_data.index,
- y=plot_data[f"QTL_{window}_{quantile}"].values,
- name=f"Quantile q={quantile}",
- line=dict(dash="dash"),
- )
- fig.update_layout(yaxis=dict(title=f"{symbol} Value"))
-
- export_data(
- export,
- os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
- "quantile",
- df_med.join(df_quantile),
- sheet_name,
- fig,
- )
-
- return fig.show(external=external_axes)
-
-
-@log_start_end(log=logger)
-def display_skew(
- symbol: str,
- data: pd.DataFrame,
- target: str,
- window: int = 14,
- export: str = "",
- sheet_name: Optional[str] = None,
- external_axes: bool = False,
-) -> Union[OpenBBFigure, None]:
- """Plots rolling skew
-
- Parameters
- ----------
- symbol: str
- Stock ticker
- data: pd.DataFrame
- Dataframe
- target: str
- Column in data to look at
- window: int
- Length of window
- sheet_name: str
- Optionally specify the name of the sheet the data is exported to.
- export: str
- Format to export data
- external_axes : bool, optional
- Whether to return the figure object or not, by default False
- """
- data = data[target]
- df_skew = rolling_model.get_skew(data, window)
-
- plot_data = pd.merge(
- data,
- df_skew,
- how="outer",
- left_index=True,
- right_index=True,
- )
-
- fig = OpenBBFigure.create_subplots(
- rows=2,
- cols=1,
- vertical_spacing=0.1,
- ).set_title(f"{symbol} Skewness Indicator")
-
- fig.add_scatter(
- x=plot_data.index,
- y=plot_data[target].values,
- name=target,
- row=1,
- col=1,
- )
-
- fig.add_scatter(
- x=plot_data.index,
- y=plot_data[f"SKEW_{window}"].values,
- name=f"Skew w={window}",
- row=2,
- col=1,
- )
-
- fig.update_layout(yaxis=dict(title=f"{target}"), yaxis2=dict(title="Indicator"))
-
- export_data(
- export,
- os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
- "skew",
- df_skew,
- sheet_name,
- fig,
- )
-
- return fig.show(external=external_axes)
-
-
-@log_start_end(log=logger)
-def display_kurtosis(
- symbol: str,
- data: pd.DataFrame,
- target: str,
- window: int = 14,
- export: str = "",
- sheet_name: Optional[str] = None,
- external_axes: bool = False,
-) -> Union[OpenBBFigure, None]:
- """Plots rolling kurtosis
-
- Parameters
- ----------
- symbol: str
- Ticker
- data: pd.DataFrame
- Dataframe of stock prices
- target: str
- Column in data to look at
- window: int
- Length of window
- sheet_name: str
- Optionally specify the name of the sheet the data is exported to.
- export: str
- Format to export data
- external_axes : bool, optional
- Whether to return the figure object or not, by default False
- """
- data = data[target]
- df_kurt = rolling_model.get_kurtosis(data, window)
-
- plot_data = pd.merge(
- data,
- df_kurt,
- how="outer",
- left_index=True,
- right_index=True,
- )
-
- fig = OpenBBFigure.create_subplots(
- rows=2,
- cols=1,
- vertical_spacing=0.1,
- subplot_titles=[f"{target}", "Kurtosis"],
- ).set_title(f"{symbol} {target} Kurtosis Indicator (window {str(window)})")
-
- fig.add_scatter(
- x=plot_data.index,
- y=plot_data[target].values,
- name=target,
- row=1,
- col=1,
- )
-
- fig.add_scatter(
- x=plot_data.index,
- y=plot_data[f"KURT_{window}"].values,
- name=f"Kurtosis w={window}",
- row=2,
- col=1,
- )
-
- fig.update_layout(yaxis=dict(title=f"{target}"), yaxis2=dict(title="Indicator"))
- fig.update_traces(showlegend=False)
-
- export_data(
- export,
- os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
- "kurtosis",
- df_kurt,
- sheet_name,
- fig,
- )
-
- return fig.show(external=external_axes)
generated by cgit v1.2.3 (git 2.25.1) at 2024-09-09 17:49:48 +0000