statsmodels.discrete.discrete_model.Probit.from_formula¶
- classmethod Probit.from_formula(formula, data, subset=None, drop_cols=None, *args, **kwargs)¶
Create a Model from a formula and dataframe.
- Parameters:
- formula
str
orgeneric
Formula
object
The formula specifying the model.
- dataarray_like
The data for the model. See Notes.
- subsetarray_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_colsarray_like
Columns to drop from the design matrix. Cannot be used to drop terms involving categoricals.
- *args
Additional positional argument that are passed to the model.
- **kwargs
These are passed to the model with one exception. The
eval_env
keyword is passed to patsy. It can be either apatsy:patsy.EvalEnvironment
object or an integer indicating the depth of the namespace to use. For example, the defaulteval_env=0
uses the calling namespace. If you wish to use a “clean” environment seteval_env=-1
.
- formula
- Returns:
model
The 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.