fklearn.data package¶
Submodules¶
fklearn.data.datasets module¶
-
fklearn.data.datasets.
make_confounded_data
(n: int) → Tuple[pandas.core.frame.DataFrame, pandas.core.frame.DataFrame, pandas.core.frame.DataFrame][source]¶ Generates fake data for counterfactual experimentation. The covariants are sex, age and severity, the treatment is a binary variable, medication and the response days until recovery.
Parameters: n (int) – The number of samples to generate Returns: - df_rnd (pd.DataFrame) – A dataframe where the treatment is randomly assigned.
- df_obs (pd.DataFrame) – A dataframe with confounding.
- df_df (pd.DataFrame) – A counter factual dataframe with confounding. Same as df_obs, but with the treatment flipped.
-
fklearn.data.datasets.
make_tutorial_data
(n: int) → pandas.core.frame.DataFrame[source]¶ Generates fake data for a tutorial. There are 3 numerical features (“num1”, “num3” and “num3”) and tow categorical features (“cat1” and “cat2”) sex, age and severity, the treatment is a binary variable, medication and the response days until recovery.
Parameters: n (int) – The number of samples to generate Returns: df – A tutorial dataset Return type: pd.DataFrame