vflow/convert.py
def dict_to_df(d: dict):
    '''Converts a dictionary with tuple keys
    into a pandas DataFrame
    '''
    d_copy = {k:d[k] for k in d if k != PREV_KEY}
    df = pd.Series(d_copy).reset_index()
    if len(d_copy.keys()) > 0:
        cols = [sk.origin for sk in list(d_copy.keys())[0]] + ['out']
        # set each init col to init-{next_module_set}
        cols = [c if c != 'init' else init_step(idx, cols) for idx, c in enumerate(cols) ]
        df.set_axis(cols, axis=1, inplace=True)
    return df
Converts a dictionary with tuple keys
    into a pandas DataFrame
    
Converts a dictionary with tuple keys
into a pandas DataFrame
Converts a dictionary with tuple keys into a pandas DataFrame
def dict_to_df(d: dict):
    d_copy = {k:d[k] for k in d if k != PREV_KEY}
    df = pd.Series(d_copy).reset_index()
    if len(d_copy.keys()) > 0:
        cols = [sk.origin for sk in list(d_copy.keys())[0]] + ['out']
        cols = [c if c != 'init' else init_step(idx, cols) for idx, c in enumerate(cols) ]
        df.set_axis(cols, axis=1, inplace=True)
    return df
def dict_to_df ( d : dict ) : d_copy = { k : d [ k ] for k in d if k != PREV_KEY } df = pd . Series ( d_copy ) . reset_index ( ) if len ( d_copy . keys ( ) ) > 0 : cols = [ sk . origin for sk in list ( d_copy . keys ( ) ) [ 0 ] ] + [ 'out' ] cols = [ c if c != 'init' else init_step ( idx , cols ) for idx , c in enumerate ( cols ) ] df . set_axis ( cols , axis = 1 , inplace = True ) return df
Converts a dictionary with tuple keys
into a pandas DataFrame
Converts a dictionary with tuple keys into a pandas DataFrame
'''Converts a dictionary with tuple keys
    into a pandas DataFrame
    ''' # set each init col to init-{next_module_set}
d
dict