clarite.modify.rowfilter_incomplete_obs¶
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clarite.modify.
rowfilter_incomplete_obs
(data, skip: Union[str, List[str], NoneType] = None, only: Union[str, List[str], NoneType] = None)¶ Remove rows containing null values
Parameters: - data: pd.DataFrame
The DataFrame to be processed and returned
- skip: str, list or None (default is None)
List of columns that are not checked for null values
- only: str, list or None (default is None)
List of columns that are the only ones to be checked for null values
Returns: - data: pd.DataFrame
The filtered DataFrame
Examples
>>> import clarite >>> nhanes_filtered = clarite.modify.rowfilter_incomplete_obs(nhanes, only=[phenotype] + covariates) ================================================================================ Running rowfilter_incomplete_obs -------------------------------------------------------------------------------- Removed 3,687 of 22,624 observations (16.30%) due to NA values in any of 8 variables