def stats(self):
        """ Returns a data frame with Sample data and state. """
        nameordered = self.samples.keys()
        nameordered.sort()

        ## Set pandas to display all samples instead of truncating
        pd.options.display.max_rows = len(self.samples)
        statdat = pd.DataFrame([self.samples[i].stats for i in nameordered],
                      index=nameordered).dropna(axis=1, how='all')
        # ensure non h,e columns print as ints
        for column in statdat:
            if column not in ["hetero_est", "error_est"]:
                statdat[column] = np.nan_to_num(statdat[column]).astype(int)
        return statdat
def stats(self):
        """ Returns a data frame with Sample data and state. """
        nameordered = self.samples.keys()
        nameordered.sort()

        ## Set pandas to display all samples instead of truncating
        pd.options.display.max_rows = len(self.samples)
        statdat = pd.DataFrame([self.samples[i].stats for i in nameordered],
                      index=nameordered).dropna(axis=1, how='all')
        # ensure non h,e columns print as ints
        for column in statdat:
            if column not in ["hetero_est", "error_est"]:
                statdat[column] = np.nan_to_num(statdat[column]).astype(int)
        return statdat
def stats ( self ) : nameordered = self . samples . keys ( ) nameordered . sort ( ) ## Set pandas to display all samples instead of truncating pd . options . display . max_rows = len ( self . samples ) statdat = pd . DataFrame ( [ self . samples [ i ] . stats for i in nameordered ] , index = nameordered ) . dropna ( axis = 1 , how = 'all' ) # ensure non h,e columns print as ints for column in statdat : if column not in [ "hetero_est" , "error_est" ] : statdat [ column ] = np . nan_to_num ( statdat [ column ] ) . astype ( int ) return statdat
Returns a data frame with Sample data and state.
Returns a data frame with Sample data and state .