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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 _create_cont_table(self,data):
 """ Create tableone for continuous data. Returns table : pandas DataFrame A table summarising the continuous variables. """

        # remove the t1_summary level
        table = self.cont_describe[['t1_summary']].copy()
        table.columns = table.columns.droplevel(level=0)

        # add a column of null counts as 1-count() from previous function
        nulltable = data[self._continuous].isnull().sum().to_frame(name='isnull')
        try:
            table = table.join(nulltable)
        except TypeError: # if columns form a CategoricalIndex, need to convert to string first
            table.columns = table.columns.astype(str)
            table = table.join(nulltable)

        # add an empty level column, for joining with cat table
        table['level'] = ''
        table.set_index([table.index,'level'],inplace=True)

        # add pval column
        if self._pval and self._pval_adjust:
            table = table.join(self._significance_table[['pval (adjusted)','ptest']])
        elif self._pval:
            table = table.join(self._significance_table[['pval','ptest']])

        return table