verdict.py
def to_df( self ):
        '''Join the innermost Dict classes into a pandas
        DataFrame, where the keys in the innermost dictionaries are the index
        and the keys for the innermost dictionaries are the column headers.
        '''

        right_depth = self.depth() == 2

        if right_depth:
            dfs = []
            for key, item in self.items():

                # Make the dataframe for each dictionary
                data = {
                    self.unpack_name: list( item.keys() ),
                    key: list( item.values() ),
                }
                df = pd.DataFrame( data )
                df.set_index( self.unpack_name, inplace=True )

                dfs.append( df )

            return pd.concat( dfs, axis=1 )

        else:
            result = {}
            for key, item in self.items():
                result[key] = item.to_df()

            return result
Join the innermost Dict classes into a pandas
        DataFrame, where the keys in the innermost dictionaries are the index
        and the keys for the innermost dictionaries are the column headers.
        
Join the innermost Dict classes into a pandas
DataFrame, where the keys in the innermost dictionaries are the index
and the keys for the innermost dictionaries are the column headers.
Join the innermost Dict classes into a pandas DataFrame where the keys in the innermost dictionaries are the index and the keys for the innermost dictionaries are the column headers .
def to_df( self ):
        right_depth = self.depth() == 2
        if right_depth:
            dfs = []
            for key, item in self.items():
                data = {
                    self.unpack_name: list( item.keys() ),
                    key: list( item.values() ),
                }
                df = pd.DataFrame( data )
                df.set_index( self.unpack_name, inplace=True )
                dfs.append( df )
            return pd.concat( dfs, axis=1 )
        else:
            result = {}
            for key, item in self.items():
                result[key] = item.to_df()
            return result
def to_df ( self ) : right_depth = self . depth ( ) == 2 if right_depth : dfs = [ ] for key , item in self . items ( ) : data = { self . unpack_name : list ( item . keys ( ) ) , key : list ( item . values ( ) ) , } df = pd . DataFrame ( data ) df . set_index ( self . unpack_name , inplace = True ) dfs . append ( df ) return pd . concat ( dfs , axis = 1 ) else : result = { } for key , item in self . items ( ) : result [ key ] = item . to_df ( ) return result
Join the innermost Dict classes into a pandas
DataFrame, where the keys in the innermost dictionaries are the index
and the keys for the innermost dictionaries are the column headers.
Join the innermost Dict classes into a pandas DataFrame where the keys in the innermost dictionaries are the index and the keys for the innermost dictionaries are the column headers .
'''Join the innermost Dict classes into a pandas
        DataFrame, where the keys in the innermost dictionaries are the index
        and the keys for the innermost dictionaries are the column headers.
        ''' # Make the dataframe for each dictionary
self