python/pymethylprocess/MethylationDataTypes.py
def merge_preprocess_sheet(self, preprocess_sample_df):
        """Feed in another phenotype dataframe that will be merged with existing phenotype array.

        Parameters
        ----------
        preprocess_sample_df
            New phenotype dataframe.
        """
        self.pheno=self.pheno.merge(preprocess_sample_df,on=['Basename'],how='inner')
        if 'disease_x' in list(self.pheno):
            self.pheno = self.pheno.rename(columns={'disease_x':'disease'})
        self.pheno = self.pheno[[col for col in list(self.pheno) if not col.startswith('Unnamed:')]]
        self.pheno=self.pheno.set_index([np.vectorize(lambda x: x.split('/')[-1])(self.pheno['Basename'])],drop=False)
Feed in another phenotype dataframe that will be merged with existing phenotype array.

        Parameters
        ----------
        preprocess_sample_df
            New phenotype dataframe.
        
Feed in another phenotype dataframe that will be merged with existing phenotype array.
Parameters

preprocess_sample_df
New phenotype dataframe.
Feed in another phenotype dataframe that will be merged with existing phenotype array . Parameters preprocess_sample_df New phenotype dataframe .
def merge_preprocess_sheet(self, preprocess_sample_df):
        self.pheno=self.pheno.merge(preprocess_sample_df,on=['Basename'],how='inner')
        if 'disease_x' in list(self.pheno):
            self.pheno = self.pheno.rename(columns={'disease_x':'disease'})
        self.pheno = self.pheno[[col for col in list(self.pheno) if not col.startswith('Unnamed:')]]
        self.pheno=self.pheno.set_index([np.vectorize(lambda x: x.split('/')[-1])(self.pheno['Basename'])],drop=False)
def merge_preprocess_sheet ( self , preprocess_sample_df ) : self . pheno = self . pheno . merge ( preprocess_sample_df , on = [ 'Basename' ] , how = 'inner' ) if 'disease_x' in list ( self . pheno ) : self . pheno = self . pheno . rename ( columns = { 'disease_x' : 'disease' } ) self . pheno = self . pheno [ [ col for col in list ( self . pheno ) if not col . startswith ( 'Unnamed:' ) ] ] self . pheno = self . pheno . set_index ( [ np . vectorize ( lambda x : x . split ( '/' ) [ - 1 ] ) ( self . pheno [ 'Basename' ] ) ] , drop = False )
Feed in another phenotype dataframe that will be merged with existing phenotype array.
Feed in another phenotype dataframe that will be merged with existing phenotype array .
"""Feed in another phenotype dataframe that will be merged with existing phenotype array.

        Parameters
        ----------
        preprocess_sample_df
            New phenotype dataframe.
        """
self
preprocess_sample_df