I have a problem with a column of my dataframe but I don't understand why there are trouble on my column cat.
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Corentin Moreau
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2`df_cat_tot['cat'].unique()` You are attempting to use `.cat` which is a reserved method for pandas. You must use `['cat']` to access that column. – piRSquared May 21 '18 at 14:08
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1In the future, please post your dataframe as text, not as an image, same goes for output/errors. – user3483203 May 21 '18 at 14:10
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Thanks for your answer, i try with df_cat_tot['cat'].unique() but I ve the same error – Corentin Moreau May 21 '18 at 14:10
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1Can you please post the output of `{type(i) for i in df_cat_tot['cat'].values}`? – jpp May 21 '18 at 14:13
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please paste your code as text, it will help to debug the code – Gautam Rai May 21 '18 at 14:14
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Input: {type(i) for i in df_cat_tot['cat'].values} Output: {pandas.core.series.Series, str} – Corentin Moreau May 21 '18 at 14:16
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Does this answer your question? ["Series objects are mutable and cannot be hashed" error](https://stackoverflow.com/questions/29700552/series-objects-are-mutable-and-cannot-be-hashed-error) – Trenton McKinney Aug 23 '20 at 18:11
2 Answers
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Your series contains other pd.Series objects. This is bad practice. In general, you should ensure your series is of a fixed type to enable you to perform manipulations without having to check for type explicitly.
Your error is due to pd.Series objects not being hashable. One workaround is to use a function to convert pd.Series objects to a hashable type such as tuple:
s = pd.Series(['one string', 'another string', pd.Series([1, 2, 3])])
def converter(x):
if isinstance(x, pd.Series):
return tuple(x.values)
else:
return x
res = s.apply(converter).unique()
print(res)
['one string' 'another string' (1, 2, 3)]
jpp
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