How to create multiple value dictionary from pandas data frame

Question

Lets say I have a pandas data frame with 2 columns(column A and Column B): For values in column 'A' there are multiple values in column 'B'. I want to create a dictionary with multiple values for each key those values should be unique as well. Please suggest me a way to do this.

Answer 1

One way is to groupby columns A:

In [1]: df = pd.DataFrame([[1, 2], [1, 4], [5, 6]], columns=['A', 'B'])

In [2]: df
Out[2]:
   A  B
0  1  2
1  1  4
2  5  6

In [3]: g = df.groupby('A')

Apply tolist on each of the group's column B:

In [4]: g['B'].tolist()  # shorthand for .apply(lambda s: s.tolist()) "automatic delegation"
Out[4]:
A
1    [2, 4]
5       [6]
dtype: object

And then call to_dict on this Series:

In [5]: g['B'].tolist().to_dict()
Out[5]: {1: [2, 4], 5: [6]}

If you want these to be unique, use unique (Note: this will create a numpy array rather than a list):

In [11]: df = pd.DataFrame([[1, 2], [1, 2], [5, 6]], columns=['A', 'B'])

In [12]: g = df.groupby('A')

In [13]: g['B'].unique()
Out[13]:
A
1    [2]
5    [6]
dtype: object

In [14]: g['B'].unique().to_dict()
Out[14]: {1: array([2]), 5: array([6])}

Other alternatives are to use .apply(lambda s: set(s)), .apply(lambda s: list(set(s))), .apply(lambda s: list(s.unique()))...