Create a nested dictionary from dataframe columns and values

Question

I have a dataframe as given below

id  DateTime              Name  Status
1   02112021 02:15:00   A   FALSE
1   02112021 02:15:00   B   TRUE
2   03112021 03:00:00   A   TRUE
2   03112021 03:00:00   B   FALSE
3   03112021 03:15:00   B   FALSE

I want to create a dictionary as given below:

dict = {'B' : { '02112021 02:15:00' : True, '03112021 03:00:00': FALSE, '03112021 03:15:00': FALSE}}

Here, B is the key came from the column Name and Keys inside the dictionary B came from the column DateTime and its values came from Status. It will take the datetime values as key and Status values as dictionary values that corresponds to B Can anyone please help, I am stucked on it.

Please fix your dictionary, this is not valid python

mozway
– mozway

2021-11-16 08:43:15 +00:00
Commented Nov 16, 2021 at 8:43 — mozway
– mozway, Commented Nov 16, 2021 at 8:43
So need remove rows with Name=A ?

jezrael
– jezrael

2021-11-16 08:48:58 +00:00
Commented Nov 16, 2021 at 8:48 — jezrael
– jezrael, Commented Nov 16, 2021 at 8:48

jezrael · Accepted Answer · 2021-11-16 09:23:51Z

1

If need nested dictionary by Name column per groups use:

d = df.groupby('Name')[['DateTime','Status']].apply(lambda x: dict(x.to_numpy())).to_dict()
print (d)
{'A': {'02112021 02:15:00': False, '03112021 03:00:00': True},
 'B': {'02112021 02:15:00': True, '03112021 03:00:00': False, '03112021 03:15:00': False}}

edited Nov 16, 2021 at 9:23

answered Nov 16, 2021 at 8:46

jezrael

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