DataFrame columns to dictionary with multiple keys and values

Question

I have the following DataFrame:

df = pd.DataFrame({
    'From':['a','b','c','d'],
    'To':['h','m','f','f'],
    'week':[1,2,3,3]
})

I want to use column 'To' and 'week' as keys to map to value 'From', create a dictionary like {(1,'h'):'a',(2,'m'):'b',(3,'f'):['c','d']}, is there a way to do this? I tried to use

dict(zip([tuple(x) for x in df[['week','To']].to_numpy()], df['From']))

but it only gives me {(1,'h'):'a',(2,'m'):'b',(3,'f'):'d'}

. If there are multiple 'From's for the same ('week', 'To'), I want to put it in a list or set. Thanks!!

Gusti Adli · Accepted Answer · 2021-05-20 16:23:55Z

1

You can use .groupby() method followed by an .apply(list) method on the column From to convert the results into a list. From here, pandas has a .to_dict() method to convert your results to a dictionary.

>>> df.groupby(['To', 'week'])['From'].apply(list).to_dict()
{('f', 3): ['c', 'd'], ('h', 1): ['a'], ('m', 2): ['b']}
>>>
>>> # use lambda to convert lists with only one value to string
>>> df.groupby(['To', 'week'])['From'].apply(lambda x: list(x) if len(x) > 1 else list(x)[0]).to_dict()
{('f', 3): ['c', 'd'], ('h', 1): 'a', ('m', 2): 'b'}

answered May 20, 2021 at 16:23

Gusti Adli

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Ank · Accepted Answer · 2021-05-20 16:44:21Z

1

Use below code to get your desired dictionary:

df.groupby(['To','week'])['From'].agg(','.join).apply(lambda s: s.split(',') if ',' in s else s).to_dict()

Output:

>>> df.groupby(['To','week'])['From'].agg(','.join).apply(lambda s: s.split(',') if ',' in s else s).to_dict()
{('f', 3): ['c', 'd'], ('h', 1): 'a', ('m', 2): 'b'}

groupby on To,Week and join the values with ,. Then just use apply to convert , separated values into lists, and finally convert the result to dictionary.

edited May 20, 2021 at 16:44

answered May 20, 2021 at 16:38

Ank

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