Panel

To obtain charts, make sure to add chart=True as the last parameter

Get underlying data

econometrics.panel(regression_type: str, regression_variables: List[Tuple], data: Dict[str, pandas.core.frame.DataFrame], entity_effects: bool = False, time_effects: bool = False) -> Tuple[pandas.core.frame.DataFrame, Any, List[Any], Any]

Based on the regression type, this function decides what regression to run.

Parameters
----------
regression_type: str
    The type of regression you wish to execute.
regression_variables : list
    The regressions variables entered where the first variable is
    the dependent variable.
data : dict
    A dictionary containing the datasets.
entity_effects: bool
    Whether to apply Fixed Effects on entities.
time_effects: bool
    Whether to apply Fixed Effects on time.

Returns
-------
The dataset used, the dependent variable, the independent variable and
the regression model.

Getting charts

econometrics.panel(data: Dict[str, pandas.core.frame.DataFrame], regression_variables: List[Tuple], regression_type: str = ‘OLS’, entity_effects: bool = False, time_effects: bool = False, export: str = ‘’, chart=True)

Based on the regression type, this function decides what regression to run.

Parameters
----------
data : dict
    A dictionary containing the datasets.
regression_variables : list
    The regressions variables entered where the first variable is
    the dependent variable.
    each column/dataset combination.
regression_type: str
    The type of regression you wish to execute. Choose from:
    OLS, POLS, RE, BOLS, FE
entity_effects: bool
    Whether to apply Fixed Effects on entities.
time_effects: bool
    Whether to apply Fixed Effects on time.
export : str
    Format to export data

Returns
-------
The dataset used, the dependent variable, the independent variable and
the regression model.