numpy.unique with order preserved

by

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

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

output:

['b' 'a' 'd' '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

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