How can I join the multiple lists in a Pandas column 'B' and get the unique values only:
A B
0 10 [x50, y-1, sss00]
1 20 [x20, MN100, x50, sss00]
2 ...
Expected output:
[x50, y-1, sss00, x20, MN100]
Get unique values from multiple lists in Pandas column
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2 Answers
You can do this simply by list comprehension and sum() method:
result=[x for x in set(df['B'].sum())]
Now If you print result you will get your desired output:
['y-1', 'x20', 'sss00', 'x50', 'MN100']
If in input data are not lists, but strings first create lists:
df.B = df.B.str.strip('[]').str.split(',')
Or:
import ast
df.B = df.B.apply(ast.literal_eval)
Use Series.explode for one Series from lists with Series.unique for remove duplicates if order is important:
L = df.B.explode().unique().tolist()
#alternative
#L = df.B.explode().drop_duplicates().tolist()
print (L)
['x50', 'y-1', 'sss00', 'x20', 'MN100']
Another idea if order is not important use set comprehension with flatten lists:
L = list(set([y for x in df.B for y in x]))
print (L)
['x50', 'MN100', 'x20', 'sss00', 'y-1']
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