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numpy.unique with order preserved

['b','b','b','a','a','c','c']

numpy.unique gives

['a','b','c']

How can I get the original order preserved

['b','a','c']

Great answers. Bonus question. Why do none of these methods work with this dataset? http://www.uploadmb.com/dw.php?id=1364341573 Here's the question numpy sort wierd behavior

Solution

  • unique() is slow, O(Nlog(N)), but you can do this by following code:

    import numpy as np
a = np.array(['b','b','b','a','a','c','c'])
_, idx = np.unique(a, return_index=True)
print(a[np.sort(idx)])

    output:

    ['b' 'a' 'c']

    Pandas.unique() is much faster for big array O(N):

    import pandas as pd

a = np.random.randint(0, 1000, 10000)
%timeit np.unique(a)
%timeit pd.unique(a)

1000 loops, best of 3: 644 us per loop
10000 loops, best of 3: 144 us per loop