如何通过文件处理从给定的数据框列中获取唯一对？

Question

sample data from dataframe:

Pairs

(8, 8), (8, 8), (8, 8), (8, 8), (8, 8)
(6, 7), (7, 7), (7, 7), (7, 6), (6, 7)
(2, 12), (12, 3), (3, 4), (4, 12), (12, 12)

    ```
    
        new_col = []
            for e in content.Pairs:
            new_col.append(list(dict.fromkeys(e)))
            content['Unique'] = new_col
    
    ```

output expected is unique pairs from Pair column like this:

(8, 8),(6, 7),(7, 6),(7, 7),(2, 12) so on

what I am getting is this result when trying the above code:

Unique

['8', '']
['6', '7', '']
['2', '12', '3', '4', '']

what is the issue with the data if I am doing with manual data then it's working why not in the data frame

Answer 1

You could use the set method:

data = (((8, 8), (8, 8), (8, 8), (8, 8), (8, 8)),
  ((6, 7), (7, 7), (7, 7), (7, 6), (6, 7)),
  ((2, 12), (12, 3), (3, 4), (4, 12), (12, 12)))

uniques = []

for col in data:
  for unique in list(set(col)):
    uniques.append(unique)

for x in uniques:
  print(x)

OR :

data = (((8, 8), (8, 8), (8, 8), (8, 8), (8, 8)),
  ((6, 7), (7, 7), (7, 7), (7, 6), (6, 7)),
  ((2, 12), (12, 3), (3, 4), (4, 12), (12, 12)))

uniques = []

for col in data:
  uniques += [unique for unique in list(set(col))]

for x in uniques:
  print(x)

Answer 2

You can use set() method to remove duplicates from the list of tuples.

 >>> items = [(8, 8), (8, 8), (8, 8), (8, 8), (8, 8),
(6, 7), (7, 7), (7, 7), (7, 6), (6, 7),
(2, 12), (12, 3), (3, 4), (4, 12), (12, 12)]
>>> set_items = set(items)
>>> set_items
{(6, 7), (7, 6), (12, 12), (7, 7), (8, 8), (4, 12), (2, 12), (3, 4), (12, 3)}