src/whylogs/mlflow/patcher.py
def log_pandas(self, df: pd.DataFrame, dataset_name: Optional[str] = None):
        """
        Log the statistics of a Pandas dataframe. Note that this method is additive
        within a run: calling this method with a specific dataset name will not generate
        a new profile; instead, data will be aggregated into the existing profile.

        In order to create a new profile, please specify a dataset_name

        :param df: the Pandas dataframe to log
        :param dataset_name: the name of the dataset (Optional). If not specified, the experiment name is used
        """
        ylogs = self._get_or_create_logger(dataset_name)

        if ylogs is None:
            logger.warning(
                "Unable to get an active logger. Are you in an active MLFlow run?"
            )

        ylogs.log_dataframe(df)

        Log the statistics of a Pandas dataframe. Note that this method is additive
        within a run: calling this method with a specific dataset name will not generate
        a new profile; instead, data will be aggregated into the existing profile.

        In order to create a new profile, please specify a dataset_name

        :param df: the Pandas dataframe to log
        :param dataset_name: the name of the dataset (Optional). If not specified, the experiment name is used
        
Log the statistics of a Pandas dataframe. Note that this method is additive
within a run: calling this method with a specific dataset name will not generate
a new profile; instead, data will be aggregated into the existing profile.

In order to create a new profile, please specify a dataset_name
Log the statistics of a Pandas dataframe . Note that this method is additive within a run : calling this method with a specific dataset name will not generate a new profile ; instead data will be aggregated into the existing profile . In order to create a new profile please specify a dataset_name
def log_pandas(self, df: pd.DataFrame, dataset_name: Optional[str] = None):
        ylogs = self._get_or_create_logger(dataset_name)
        if ylogs is None:
            logger.warning(
                "Unable to get an active logger. Are you in an active MLFlow run?"
            )
        ylogs.log_dataframe(df)
def log_pandas ( self , df : pd . DataFrame , dataset_name : Optional [ str ] = None ) : ylogs = self . _get_or_create_logger ( dataset_name ) if ylogs is None : logger . warning ( "Unable to get an active logger. Are you in an active MLFlow run?" ) ylogs . log_dataframe ( df )
Log the statistics of a Pandas dataframe.
Log the statistics of a Pandas dataframe .
"""
        Log the statistics of a Pandas dataframe. Note that this method is additive
        within a run: calling this method with a specific dataset name will not generate
        a new profile; instead, data will be aggregated into the existing profile.

        In order to create a new profile, please specify a dataset_name

        :param df: the Pandas dataframe to log
        :param dataset_name: the name of the dataset (Optional). If not specified, the experiment name is used
        """
self
df
pd.DataFrame
the Pandas dataframe to log
the Pandas dataframe to log
dataset_name
Optional[str]
the name of the dataset (Optional). If not specified, the experiment name is used
the name of the dataset ( Optional ) . If not specified the experiment name is used