clarite.modify.colfilter¶
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clarite.modify.
colfilter
(data, skip: Union[str, List[str], None] = None, only: Union[str, List[str], None] = None)¶ Remove some variables (skip) or keep only certain variables (only)
Parameters: - data: pd.DataFrame
The DataFrame to be processed and returned
- skip: str, list or None (default is None)
List of variables to remove
- only: str, list or None (default is None)
List of variables to keep
Returns: - data: pd.DataFrame
The filtered DataFrame
Examples
>>> import clarite >>> female_logBMI = clarite.modify.colfilter(nhanes, only=['BMXBMI', 'female']) ================================================================================ Running colfilter -------------------------------------------------------------------------------- Keeping 2 of 945 variables: 0 of 0 binary variables 0 of 0 categorical variables 2 of 945 continuous variables 0 of 0 unknown variables ================================================================================