statsmodels.base.model.LikelihoodModel.from_formula

LikelihoodModel.from_formula(formula, data, subset=None, drop_cols=None, *args, **kwargs)

Create a Model from a formula and dataframe.

Parameters:

formula : str or generic Formula object

The formula specifying the model

data : array-like

The data for the model. See Notes.

subset : array-like

An array-like object of booleans, integers, or index values that indicate the subset of df to use in the model. Assumes df is a pandas.DataFrame

drop_cols : array-like

Columns to drop from the design matrix. Cannot be used to drop terms involving categoricals.

args : extra arguments

These are passed to the model

kwargs : extra keyword arguments

These are passed to the model with one exception. The eval_env keyword is passed to patsy. It can be either a patsy.EvalEnvironment object or an integer indicating the depth of the namespace to use. For example, the default eval_env=0 uses the calling namespace. If you wish to use a “clean” environment set eval_env=-1.

Returns:

model : Model instance

Notes

data must define __getitem__ with the keys in the formula terms args and kwargs are passed on to the model instantiation. E.g., a numpy structured or rec array, a dictionary, or a pandas DataFrame.