def identify_missing(self, df, check_start=True):
        """ Identify missing data.

        Parameters
        ----------
        df              : pd.DataFrame()
            Dataframe to check for missing data.
        check_start     : bool
            turns 0 to 1 for the first observation, to display the start of the data
        as the beginning of the missing data event

        Returns
        -------
        pd.DataFrame(), str
            dataframe where 1 indicates missing data and 0 indicates reported data,
        returns the column name generated from the MDAL Query

        """

        # Check start changes the first value of df to 1, when the data stream is initially missing
        # This allows the diff function to acknowledge the missing data
        data_missing = df.isnull() * 1
        col_name = str(data_missing.columns[0])

        # When there is no data stream at the beginning we change it to 1
        if check_start & data_missing[col_name][0] == 1:
            data_missing[col_name][0] = 0

        return data_missing, col_name
Identify missing data.

        Parameters
        ----------
        df              : pd.DataFrame()
            Dataframe to check for missing data.
        check_start     : bool
            turns 0 to 1 for the first observation, to display the start of the data
        as the beginning of the missing data event

        Returns
        -------
        pd.DataFrame(), str
            dataframe where 1 indicates missing data and 0 indicates reported data,
        returns the column name generated from the MDAL Query