azureml/__init__.py
def _update_from_dataframe(self, dataframe, data_type_id=None, name=None,
                              description=None):
        """
        Serialize the specified DataFrame and replace the existing dataset.

        Parameters
        ----------
        dataframe : pandas.DataFrame
            Data to serialize.
        data_type_id : str, optional
            Format to serialize to.
            If None, the existing format is preserved.
            Supported formats are:
                'PlainText'
                'GenericCSV'
                'GenericTSV'
                'GenericCSVNoHeader'
                'GenericTSVNoHeader'
            See the azureml.DataTypeIds class for constants.
        name : str, optional
            Name for the dataset.
            If None, the name of the existing dataset is used.
        description : str, optional
            Description for the dataset.
            If None, the name of the existing dataset is used.
        """
        _not_none('dataframe', dataframe)

        if data_type_id is None:
            data_type_id = self.data_type_id
        if name is None:
            name = self.name
        if description is None:
            description = self.description

        try:
            output = BytesIO()
            serialize_dataframe(output, data_type_id, dataframe)
            raw_data = output.getvalue()
        finally:
            output.close()

        self._upload_and_refresh(raw_data, data_type_id, name, description)
def _update_from_dataframe(self, dataframe, data_type_id=None, name=None,
                              description=None):
        _not_none('dataframe', dataframe)

        if data_type_id is None:
            data_type_id = self.data_type_id
        if name is None:
            name = self.name
        if description is None:
            description = self.description

        try:
            output = BytesIO()
            serialize_dataframe(output, data_type_id, dataframe)
            raw_data = output.getvalue()
        finally:
            output.close()

        self._upload_and_refresh(raw_data, data_type_id, name, description)
def _update_from_dataframe ( self , dataframe , data_type_id = None , name = None , description = None ) : _not_none ( 'dataframe' , dataframe ) if data_type_id is None : data_type_id = self . data_type_id if name is None : name = self . name if description is None : description = self . description try : output = BytesIO ( ) serialize_dataframe ( output , data_type_id , dataframe ) raw_data = output . getvalue ( ) finally : output . close ( ) self . _upload_and_refresh ( raw_data , data_type_id , name , description )
Serialize the specified DataFrame and replace the existing dataset.

        Parameters
        ----------
        dataframe : pandas.DataFrame
            Data to serialize.
        data_type_id : str, optional
            Format to serialize to.
            If None, the existing format is preserved.
            Supported formats are:
                'PlainText'
                'GenericCSV'
                'GenericTSV'
                'GenericCSVNoHeader'
                'GenericTSVNoHeader'
            See the azureml.DataTypeIds class for constants.
        name : str, optional
            Name for the dataset.
            If None, the name of the existing dataset is used.
        description : str, optional
            Description for the dataset.
            If None, the name of the existing dataset is used.
Serialize the specified DataFrame and replace the existing dataset .