Dictionary sometimes featuring with multiple keys

Question

I have a pandas data frame, and I would like to make a new column/s based on the dictionary values.

Here is my df and dictionary:

data = ['One', 'Two', 'Three', 'Four']

df = pd.DataFrame(data, columns=['Count'])

dictionary = {'One':'Red', 'Two':['Red', 'Blue'], 'Three':'Green','Four':['Green','Red', 'Blue']}

This is the result I would like to achieve,

Preferably with blank fields instead of None values, does anybody know a way?

I tried the below:

df = df = pd.DataFrame([(k, *v) for k, v in dictionary.items()])
df.columns = ['name'] + [f'n{x}' for x in df.columns[1:]]
df

However, for keys that do not have multiple values, it seems to split the actual string per letter over the columns like so:

A solution where it maps the values to one columns separated with a delimiter (,) would also be helpful.

Answer 1

There are lists in values of dictionary, so need if-else statement for prevent unpack strings by *:

df = pd.DataFrame([(k, *v) 
                   if isinstance(v, list) 
                   else (k, v) for k, v in dictionary.items()])
df.columns = ['name'] + [f'n{x}' for x in df.columns[1:]]
print (df)
    name     n1    n2    n3
0    One    Red  None  None
1    Two    Red  Blue  None
2  Three  Green  None  None
3   Four  Green   Red  Blue

Details:

print (((*'Red', )))
('R', 'e', 'd')

print (((*['Red', 'Blue'], )))
('Red', 'Blue')

Preferably with blank fields instead of None values, does anybody know a way?

Add DataFrame.fillna:

df = pd.DataFrame([(k, *v) 
                   if isinstance(v, list) 
                   else (k, v) 
                   for k, v in dictionary.items()]).fillna('')
df.columns = ['name'] + [f'n{x}' for x in df.columns[1:]]
print (df)
    name     n1    n2    n3
0    One    Red            
1    Two    Red  Blue      
2  Three  Green            
3   Four  Green   Red  Blue

If same indices and number of rows use DataFrame.join:

If original df_orig has different like default RangeIndex add index=df_orig.index to DataFrame constructor:

df = pd.DataFrame([(k, *v) 
                   if isinstance(v, list) 
                   else (k, v) 
                   for k, v in dictionary.items()], index=df_orig.index).fillna('')
df.columns = ['name'] + [f'n{x}' for x in df.columns[1:]]

df = df_orig.join(df)

If need merge by name column by left join in DataFrame.merge:

df = df_orig.merge(df, on='name', how='left')