explann package

Subpackages

Submodules

explann.dataio module

class explann.dataio.BaseImport(data: DataFrame = None, start_index: int = 1)[source]

Bases: object

Base class for importing data from a file or string.

data : pandas.DataFrame Data to be imported.

data
Type:

pandas.DataFrame

parsed_data
Type:

pandas.DataFrame

levels
Type:

pandas.DataFrame

delimiter
Type:

str

parse_levels(data)[source]

Parse levels from a pandas.DataFrame.

parse_levels_from_string(data, delimiter)[source]

Parse levels from a string.

parse_levels_from_xlsx(path, sheet_name, index_col)[source]

Parse levels from an xlsx file.

parse_levels(data: DataFrame = None)[source]
parse_levels_from_string(data: str = None, delimiter: str = None)[source]
parse_levels_from_xlsx(data: str = None, sheet_name: str = None, index_col: int = 0)[source]
class explann.dataio.ImportString(data: str = None, levels: str = None, delimiter: str = '\\s', engine: str = 'python', start_index: int = 1, **kwargs)[source]

Bases: BaseImport

class explann.dataio.ImportXLSX(path: str = None, data_sheet: str = 0, levels_sheet: str = None, start_index: int = 1, **kwargs)[source]

Bases: BaseImport

explann.models module

class explann.models.BaseModel[source]

Bases: object

class explann.models.FactorialModel(data: ~pandas.core.frame.DataFrame = None, functions: str | list | tuple = None, statsmodel: object = <bound method Model.from_formula of <class 'statsmodels.regression.linear_model.OLS'>>, levels: ~pandas.core.frame.DataFrame = None, **fit_kwargs)[source]

Bases: BaseModel

anova(function: str | list | tuple = None)[source]
build_significant_models(function: str | list | tuple = None, alpha: float = 0.05, use_anova: bool = False)[source]
decode_variables(variables, levels: DataFrame = None)[source]
property dependent_variables
encode_variables(variables, levels: DataFrame = None)[source]
fit(data: ~pandas.core.frame.DataFrame = None, functions: str | list | tuple = None, statsmodel: object = <bound method Model.from_formula of <class 'statsmodels.regression.linear_model.OLS'>>, **fit_kwargs)[source]
property function_names
get_categorical_functions()[source]
get_categorical_model()[source]
get_significant_model_functions(function: str | list | tuple = None, alpha: float = 0.05, use_anova: bool = False)[source]
get_significant_terms(function: str | list | tuple = None, alpha: float = 0.05)[source]
property independent_variables
lack_of_fit(function: str | list | tuple = None, baseline: BaseModel = None, alpha: float = 0.05)[source]
predict(function, variables)[source]
predict_rescaled(function, variables, levels: DataFrame = None)[source]
print_equation(function: str | list | tuple = None, alpha: float = 0.05, precision: int = 4)[source]
summary(function: str | list | tuple = None)[source]
working_lack_of_fit(function: str | list | tuple = None, baseline: BaseModel = None)[source]
explann.models.add_categorical(formula)[source]

Module contents