mirror of
https://github.com/OpenBB-finance/OpenBB.git
synced 2026-11-12 12:22:35 +00:00
Another attempt to resolve even more linting errors
This commit is contained in:
@@ -38,7 +38,6 @@ Extensions:
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- fmp@0.1.0a2
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- fred@0.1.0a2
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- intrinio@0.1.0a2
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- oecd@0.1.0a2
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- polygon@0.1.0a2
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- quandl@0.1.0a2
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- yfinance@0.1.0a2 """
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@@ -53,6 +53,7 @@ class ROUTER_econometrics(Container):
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List of columns to use as exogenous variables.
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lags: PositiveInt
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Number of lags to use in the test.
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Returns
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-------
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OBBject[Data]
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@@ -85,6 +86,7 @@ class ROUTER_econometrics(Container):
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Data columns to check cointegration
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maxlag: PositiveInt
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Number of lags to use in the test.
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Returns
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-------
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OBBject[Data]
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@@ -132,7 +134,7 @@ class ROUTER_econometrics(Container):
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y_column: str,
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x_columns: List[str],
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) -> OBBject[Dict]:
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"""Perform Durbin-Watson test for autocorrelation
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"""Perform Durbin-Watson test for autocorrelation.
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Parameters
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----------
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@@ -180,6 +182,7 @@ class ROUTER_econometrics(Container):
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Columns to use as exogenous variables.
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lag: PositiveInt
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Number of lags to use in the test.
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Returns
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-------
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OBBject[Data]
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@@ -275,7 +278,7 @@ class ROUTER_econometrics(Container):
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y_column: str,
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x_columns: List[str],
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) -> OBBject[Dict]:
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"""Perform a Between estimator regression on panel data
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"""Perform a Between estimator regression on panel data.
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Parameters
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----------
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@@ -310,7 +313,7 @@ class ROUTER_econometrics(Container):
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y_column: str,
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x_columns: List[str],
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) -> OBBject[Dict]:
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"""Perform a first-difference estimate for panel data
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"""Perform a first-difference estimate for panel data.
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Parameters
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----------
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@@ -345,7 +348,7 @@ class ROUTER_econometrics(Container):
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y_column: str,
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x_columns: List[str],
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) -> OBBject[Dict]:
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"""Fama-MacBeth estimator for panel data
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"""Fama-MacBeth estimator for panel data.
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Parameters
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----------
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@@ -380,7 +383,7 @@ class ROUTER_econometrics(Container):
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y_column: str,
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x_columns: List[str],
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) -> OBBject[Dict]:
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"""One- and two-way fixed effects estimator for panel data
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"""One- and two-way fixed effects estimator for panel data.
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Parameters
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----------
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@@ -415,7 +418,7 @@ class ROUTER_econometrics(Container):
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y_column: str,
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x_columns: List[str],
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) -> OBBject[Dict]:
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"""Perform a Pooled coefficvient estimator regression on panel data
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"""Perform a Pooled coefficvient estimator regression on panel data.
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Parameters
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----------
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@@ -450,7 +453,7 @@ class ROUTER_econometrics(Container):
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y_column: str,
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x_columns: List[str],
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) -> OBBject[Dict]:
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"""Perform One-way Random Effects model for panel data
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"""Perform One-way Random Effects model for panel data.
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Parameters
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----------
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@@ -496,6 +499,7 @@ class ROUTER_econometrics(Container):
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regression: str
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Regression type to use in the test. Either "c" for constant only, "ct" for constant and trend, or "ctt" for
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constant, trend, and trend-squared.
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Returns
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-------
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OBBject[Data]
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@@ -22,9 +22,6 @@ class ROUTER_economy(Container):
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european_index
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european_index_constituents
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fred_index
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gdpforecast
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gdpnom
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gdpreal
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index
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index_search
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index_snapshots
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@@ -741,252 +738,6 @@ class ROUTER_economy(Container):
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**inputs,
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)
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@validate_call
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def gdpforecast(
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self,
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period: Annotated[
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Literal["quarter", "annual"],
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OpenBBCustomParameter(
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description="Units for nominal GDP period. Either quarter or annual."
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),
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] = "annual",
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start_date: Annotated[
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Union[datetime.date, None, str],
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OpenBBCustomParameter(
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description="Start date of the data, in YYYY-MM-DD format."
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),
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] = None,
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end_date: Annotated[
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Union[datetime.date, None, str],
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OpenBBCustomParameter(
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description="End date of the data, in YYYY-MM-DD format."
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),
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] = None,
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type: Annotated[
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Literal["nominal", "real"],
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OpenBBCustomParameter(
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description="Type of GDP to get forecast of. Either nominal or real."
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),
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] = "real",
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provider: Optional[Literal["oecd"]] = None,
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**kwargs
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) -> OBBject[List[Data]]:
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"""GDP Data.
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Parameters
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----------
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period : Literal['quarter', 'annual']
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Units for nominal GDP period. Either quarter or annual.
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start_date : Optional[datetime.date]
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Start date of the data, in YYYY-MM-DD format.
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end_date : Optional[datetime.date]
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End date of the data, in YYYY-MM-DD format.
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type : Literal['nominal', 'real']
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Type of GDP to get forecast of. Either nominal or real.
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provider : Optional[Literal['oecd']]
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The provider to use for the query, by default None.
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If None, the provider specified in defaults is selected or 'oecd' if there is
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no default.
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country : Literal['argentina', 'asia', 'australia', 'austria', 'belgium', 'brazil', 'bulgaria', 'canada', 'chile', 'china', 'colombia', 'costa_rica', 'croatia', 'czech_republic', 'denmark', 'estonia', 'euro_area_17', 'finland', 'france', 'germany', 'greece', 'hungary', 'iceland', 'india', 'indonesia', 'ireland', 'israel', 'italy', 'japan', 'korea', 'latvia', 'lithuania', 'luxembourg', 'mexico', 'netherlands', 'new_zealand', 'non-oecd', 'norway', 'oecd_total', 'peru', 'poland', 'portugal', 'romania', 'russia', 'slovak_republic', 'slovenia', 'south_africa', 'spain', 'sweden', 'switzerland', 'turkey', 'united_kingdom', 'united_states', 'world']
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Country to get GDP for. (provider: oecd)
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Returns
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-------
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OBBject
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results : List[GDPForecast]
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Serializable results.
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provider : Optional[Literal['oecd']]
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Provider name.
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warnings : Optional[List[Warning_]]
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List of warnings.
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chart : Optional[Chart]
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Chart object.
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extra: Dict[str, Any]
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Extra info.
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GDPForecast
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-----------
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date : Optional[date]
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The date of the data.
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value : Optional[float]
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Nominal GDP value on the date.""" # noqa: E501
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inputs = filter_inputs(
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provider_choices={
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"provider": provider,
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},
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standard_params={
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"period": period,
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"start_date": start_date,
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"end_date": end_date,
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"type": type,
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},
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extra_params=kwargs,
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)
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return self._run(
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"/economy/gdpforecast",
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**inputs,
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)
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@validate_call
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def gdpnom(
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self,
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units: Annotated[
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Literal["usd", "usd_cap"],
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OpenBBCustomParameter(
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description="Units to get nominal GDP in. Either usd or usd_cap indicating per capita."
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),
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] = "usd",
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start_date: Annotated[
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Union[datetime.date, None, str],
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OpenBBCustomParameter(
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description="Start date of the data, in YYYY-MM-DD format."
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),
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] = None,
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end_date: Annotated[
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Union[datetime.date, None, str],
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OpenBBCustomParameter(
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description="End date of the data, in YYYY-MM-DD format."
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),
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] = None,
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provider: Optional[Literal["oecd"]] = None,
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**kwargs
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) -> OBBject[List[Data]]:
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"""GDP Data.
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Parameters
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----------
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units : Literal['usd', 'usd_cap']
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Units to get nominal GDP in. Either usd or usd_cap indicating per capita.
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start_date : Optional[datetime.date]
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Start date of the data, in YYYY-MM-DD format.
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end_date : Optional[datetime.date]
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End date of the data, in YYYY-MM-DD format.
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provider : Optional[Literal['oecd']]
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The provider to use for the query, by default None.
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If None, the provider specified in defaults is selected or 'oecd' if there is
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no default.
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country : Literal['australia', 'austria', 'belgium', 'brazil', 'canada', 'chile', 'colombia', 'costa_rica', 'czech_republic', 'denmark', 'estonia', 'euro_area', 'european_union', 'finland', 'france', 'germany', 'greece', 'hungary', 'iceland', 'indonesia', 'ireland', 'israel', 'italy', 'japan', 'korea', 'latvia', 'lithuania', 'luxembourg', 'mexico', 'netherlands', 'new_zealand', 'norway', 'poland', 'portugal', 'russia', 'slovak_republic', 'slovenia', 'south_africa', 'spain', 'sweden', 'switzerland', 'turkey', 'united_kingdom', 'united_states']
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Country to get GDP for. (provider: oecd)
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Returns
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-------
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OBBject
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results : List[GDPNom]
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Serializable results.
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provider : Optional[Literal['oecd']]
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Provider name.
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warnings : Optional[List[Warning_]]
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List of warnings.
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chart : Optional[Chart]
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Chart object.
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extra: Dict[str, Any]
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Extra info.
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GDPNom
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------
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date : Optional[date]
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The date of the data.
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value : Optional[float]
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Nominal GDP value on the date.""" # noqa: E501
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inputs = filter_inputs(
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provider_choices={
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"provider": provider,
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},
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standard_params={
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"units": units,
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"start_date": start_date,
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"end_date": end_date,
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},
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extra_params=kwargs,
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)
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return self._run(
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"/economy/gdpnom",
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**inputs,
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)
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@validate_call
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def gdpreal(
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self,
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units: Annotated[
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Literal["idx", "qoq", "yoy"],
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OpenBBCustomParameter(
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description="Units to get real GDP in. Either idx (indicating 2015=100), qoq (previous period) or yoy (same period, previous year).)"
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),
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] = "yoy",
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start_date: Annotated[
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Union[datetime.date, None, str],
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OpenBBCustomParameter(
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description="Start date of the data, in YYYY-MM-DD format."
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),
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] = None,
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end_date: Annotated[
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Union[datetime.date, None, str],
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OpenBBCustomParameter(
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description="End date of the data, in YYYY-MM-DD format."
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),
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] = None,
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provider: Optional[Literal["oecd"]] = None,
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**kwargs
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) -> OBBject[List[Data]]:
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"""GDP Data.
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Parameters
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----------
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units : Literal['idx', 'qoq', 'yoy']
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Units to get real GDP in. Either idx (indicating 2015=100), qoq (previous period) or yoy (same period, previous year).)
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start_date : Optional[datetime.date]
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Start date of the data, in YYYY-MM-DD format.
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end_date : Optional[datetime.date]
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End date of the data, in YYYY-MM-DD format.
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provider : Optional[Literal['oecd']]
|
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The provider to use for the query, by default None.
|
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If None, the provider specified in defaults is selected or 'oecd' if there is
|
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no default.
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country : Literal['G20', 'G7', 'argentina', 'australia', 'austria', 'belgium', 'brazil', 'bulgaria', 'canada', 'chile', 'china', 'colombia', 'costa_rica', 'croatia', 'czech_republic', 'denmark', 'estonia', 'euro_area_19', 'europe', 'european_union_27', 'finland', 'france', 'germany', 'greece', 'hungary', 'iceland', 'india', 'indonesia', 'ireland', 'israel', 'italy', 'japan', 'korea', 'latvia', 'lithuania', 'luxembourg', 'mexico', 'netherlands', 'new_zealand', 'norway', 'oecd_total', 'poland', 'portugal', 'romania', 'russia', 'saudi_arabia', 'slovak_republic', 'slovenia', 'south_africa', 'spain', 'sweden', 'switzerland', 'turkey', 'united_kingdom', 'united_states']
|
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Country to get GDP for. (provider: oecd)
|
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|
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Returns
|
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-------
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OBBject
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results : List[GDPReal]
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Serializable results.
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provider : Optional[Literal['oecd']]
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Provider name.
|
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warnings : Optional[List[Warning_]]
|
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List of warnings.
|
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chart : Optional[Chart]
|
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Chart object.
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extra: Dict[str, Any]
|
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Extra info.
|
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GDPReal
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-------
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date : Optional[date]
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The date of the data.
|
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value : Optional[float]
|
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Nominal GDP value on the date.""" # noqa: E501
|
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|
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inputs = filter_inputs(
|
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provider_choices={
|
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"provider": provider,
|
||||
},
|
||||
standard_params={
|
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"units": units,
|
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"start_date": start_date,
|
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"end_date": end_date,
|
||||
},
|
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extra_params=kwargs,
|
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)
|
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|
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return self._run(
|
||||
"/economy/gdpreal",
|
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**inputs,
|
||||
)
|
||||
|
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@validate_call
|
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def index(
|
||||
self,
|
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|
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@@ -19,7 +19,6 @@
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"fmp@0.1.0a2",
|
||||
"fred@0.1.0a2",
|
||||
"intrinio@0.1.0a2",
|
||||
"oecd@0.1.0a2",
|
||||
"polygon@0.1.0a2",
|
||||
"quandl@0.1.0a2",
|
||||
"yfinance@0.1.0a2"
|
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|
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@@ -26,9 +26,6 @@
|
||||
"economy_european_index": "/economy/european_index",
|
||||
"economy_european_index_constituents": "/economy/european_index_constituents",
|
||||
"economy_fred_index": "/economy/fred_index",
|
||||
"economy_gdpforecast": "/economy/gdpforecast",
|
||||
"economy_gdpnom": "/economy/gdpnom",
|
||||
"economy_gdpreal": "/economy/gdpreal",
|
||||
"economy_index": "/economy/index",
|
||||
"economy_index_search": "/economy/index_search",
|
||||
"economy_index_snapshots": "/economy/index_snapshots",
|
||||
|
||||
@@ -40,7 +40,7 @@ class ROUTER_qa(Container):
|
||||
def capm(
|
||||
self, data: Union[List[Data], pandas.DataFrame], target: str
|
||||
) -> OBBject[CAPMModel]:
|
||||
"""Capital Asset Pricing Model.""" # noqa: E501
|
||||
"""Get Capital Asset Pricing Model.""" # noqa: E501
|
||||
|
||||
inputs = filter_inputs(
|
||||
data=data,
|
||||
@@ -59,7 +59,7 @@ class ROUTER_qa(Container):
|
||||
target: str,
|
||||
window: Annotated[int, Gt(gt=0)],
|
||||
) -> OBBject[List[Data]]:
|
||||
"""Kurtosis.
|
||||
"""Get the Kurtosis.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
@@ -91,8 +91,7 @@ class ROUTER_qa(Container):
|
||||
def normality(
|
||||
self, data: Union[List[Data], pandas.DataFrame], target: str
|
||||
) -> OBBject[NormalityModel]:
|
||||
"""
|
||||
Normality Statistics.
|
||||
"""Get Normality Statistics.
|
||||
|
||||
- **Kurtosis**: whether the kurtosis of a sample differs from the normal distribution.
|
||||
- **Skewness**: whether the skewness of a sample differs from the normal distribution.
|
||||
@@ -131,7 +130,7 @@ class ROUTER_qa(Container):
|
||||
threshold_start: float = 0.0,
|
||||
threshold_end: float = 1.5,
|
||||
) -> OBBject[List[OmegaModel]]:
|
||||
"""Omega Ratio.
|
||||
"""Calculate the Omega Ratio.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
@@ -170,7 +169,24 @@ class ROUTER_qa(Container):
|
||||
window: Annotated[int, Gt(gt=0)],
|
||||
quantile_pct: Annotated[float, Ge(ge=0)] = 0.5,
|
||||
) -> OBBject[List[Data]]:
|
||||
"""Quantile.""" # noqa: E501
|
||||
"""Get Quantile.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
data : List[Data]
|
||||
Time series data.
|
||||
target : str
|
||||
Target column name.
|
||||
window : PositiveInt
|
||||
Window size.
|
||||
quantile_pct : NonNegativeFloat, optional
|
||||
Quantile percentage, by default 0.5
|
||||
|
||||
Returns
|
||||
-------
|
||||
OBBject[List[Data]]
|
||||
Quantile.
|
||||
""" # noqa: E501
|
||||
|
||||
inputs = filter_inputs(
|
||||
data=data,
|
||||
@@ -192,7 +208,7 @@ class ROUTER_qa(Container):
|
||||
rfr: float = 0.0,
|
||||
window: Annotated[int, Gt(gt=0)] = 252,
|
||||
) -> OBBject[List[Data]]:
|
||||
"""Sharpe Ratio.
|
||||
"""Get Sharpe Ratio.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
@@ -230,7 +246,7 @@ class ROUTER_qa(Container):
|
||||
target: str,
|
||||
window: Annotated[int, Gt(gt=0)],
|
||||
) -> OBBject[List[Data]]:
|
||||
"""Skewness.
|
||||
"""Get Skewness.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
@@ -267,7 +283,7 @@ class ROUTER_qa(Container):
|
||||
window: Annotated[int, Gt(gt=0)] = 252,
|
||||
adjusted: bool = False,
|
||||
) -> OBBject[List[Data]]:
|
||||
"""Sortino Ratio.
|
||||
"""Get Sortino Ratio.
|
||||
|
||||
For method & terminology see: http://www.redrockcapital.com/Sortino__A__Sharper__Ratio_Red_Rock_Capital.pdf
|
||||
|
||||
@@ -307,7 +323,7 @@ class ROUTER_qa(Container):
|
||||
def summary(
|
||||
self, data: Union[List[Data], pandas.DataFrame], target: str
|
||||
) -> OBBject[SummaryModel]:
|
||||
"""Summary.
|
||||
"""Get Summary Statistics.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
@@ -340,7 +356,7 @@ class ROUTER_qa(Container):
|
||||
fuller_reg: Literal["c", "ct", "ctt", "nc"] = "c",
|
||||
kpss_reg: Literal["c", "ct"] = "c",
|
||||
) -> OBBject[UnitRootModel]:
|
||||
"""Unit Root Test.
|
||||
"""Get Unit Root Test.
|
||||
|
||||
Augmented Dickey-Fuller test for unit root.
|
||||
Kwiatkowski-Phillips-Schmidt-Shin test for unit root.
|
||||
|
||||
@@ -612,8 +612,8 @@ class ROUTER_ta(Container):
|
||||
data: Union[List[Data], pandas.DataFrame],
|
||||
index: str = "date",
|
||||
target: str = "close",
|
||||
show_all: bool = False,
|
||||
asint: bool = False,
|
||||
show_all: bool = True,
|
||||
asint: bool = True,
|
||||
offset: int = 0,
|
||||
) -> OBBject[List[Data]]:
|
||||
"""
|
||||
@@ -630,7 +630,7 @@ class ROUTER_ta(Container):
|
||||
show_all : bool, optional
|
||||
Show 1 - 13. If set to False, show 6 - 9
|
||||
asint : bool, optional
|
||||
If True, fill NAs with 0 and change type to int, by default False
|
||||
If True, fill NAs with 0 and change type to int, by default True.
|
||||
offset : int, optional
|
||||
How many periods to offset the result
|
||||
|
||||
|
||||
@@ -11,7 +11,6 @@ from openbb_core.api.auth.user import (
|
||||
get_user_settings,
|
||||
)
|
||||
|
||||
|
||||
# ruff: noqa: S105 S106
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user