Creating Dict from DataFrame

Question

I'm trying to create dictionary from DF however I'm not getting the desired output:

DataFrame:

A      B   C    D  
0.0   0.0 NaN  NaN 
0.0   0.0 NaN  NaN 
0.0   0.0 NaN  NaN 
0.0   0.0 NaN  NaN 
0.0   0.0 NaN  NaN 

data_dict1 = adsl.to_dict('list')

Current output: {'A': [0.0, 0.0, 0.0, 0.0, 0.0, 0.0]}

Desired output: {'A': {0.0, 0.0, 0.0, 0.0, 0.0, 0.0}}

Difference is square braces instead of curly braces.

Answer 1

If you have an example df , created from a dict :

data = {'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd']}
df = pd.DataFrame.from_dict(data)

---

You can do:

data_dict = df.to_dict('dict')

---

data_dict will be:

{'col_1': {0: 3, 1: 2, 2: 1, 3: 0}, 'col_2': {0: 'a', 1: 'b', 2: 'c', 3: 'd'}}

If you want to keep only col_1 , you can, using this , delete col_2 from data_dict :

data_dict.pop('col_2',None)

Your new data_dict will be:

{'col_1': {0: 3, 1: 2, 2: 1, 3: 0}}

Answer 2

Your current output is already a dictionary, mapping 'A' to [0.0,0.0,....].

This is not a valid python expression:

{'A':{0.0,0.0,....}}

But

data_dict = df.to_dict() 

Should give you what you are looking for.

Answer 3

Based on your comment reply it seems you ARE looking for a unique set of values for each column. Try:

data_dict1 = adsl.to_dict('list') # which you already have, then...
data_dict1 = {key: set(vals) for key, vals in data_dict1.items()}

This will give you what you're asking for BUT it is bound to lose any sorting you have on the dataframe.