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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 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