I am trying to use drop_duplicates method on my dataframe, but I am getting an error. See the following:
error: TypeError: unhashable type: \'list\'<
@Allen's answer is great, but have a little problem.
df.iloc[df.astype(str).drop_duplicates().index]
it should be loc not iloc.loot at the example.
a = pd.DataFrame([['a',18],['b',11],['a',18]],index=[4,6,8])
Out[52]:
0 1
4 a 18
6 b 11
8 a 18
a.iloc[a.astype(str).drop_duplicates().index]
Out[53]:
...
IndexError: positional indexers are out-of-bounds
a.loc[a.astype(str).drop_duplicates().index]
Out[54]:
0 1
4 a 18
6 b 11
Overview: you can see which rows are duplicated
Method 1:
df2=df.copy()
mylist=df2.iloc[0,1]
df2.iloc[0,1]=' '.join(map(str,mylist))
mylist=df2.iloc[1,1]
df2.iloc[1,1]=' '.join(map(str,mylist))
duplicates=df2.duplicated(keep=False)
print(df2[duplicates])
Method 2:
print(df.astype(str).duplicated(keep=False))
drop_duplicates won't work with lists in your dataframe as the error message implies. However, you can drop duplicates on the dataframe casted as str and then extract the rows from original df using the index from the results.
Setup
df = pd.DataFrame({'Keyword': {0: 'apply', 1: 'apply', 2: 'apply', 3: 'terms', 4: 'terms'},
'X': {0: [1, 2], 1: [1, 2], 2: 'xy', 3: 'xx', 4: 'yy'},
'Y': {0: 'yy', 1: 'yy', 2: 'yx', 3: 'ix', 4: 'xi'}})
#Drop directly causes the same error
df.drop_duplicates()
Traceback (most recent call last):
...
TypeError: unhashable type: 'list'
Solution
#convert hte df to str type, drop duplicates and then select the rows from original df.
df.loc[df.astype(str).drop_duplicates().index]
Out[205]:
Keyword X Y
0 apply [1, 2] yy
2 apply xy yx
3 terms xx ix
4 terms yy xi
#the list elements are still list in the final results.
df.loc[df.astype(str).drop_duplicates().index].loc[0,'X']
Out[207]: [1, 2]
Edit: replaced iloc with loc. In this particular case, both work as the index matches the positional index, but it is not general