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In [1]:

    
import numpy as np



In [2]:

    
a = np.array([0, 0, 30, 10, 10, 20])
print(a)









    



[ 0  0 30 10 10 20]



In [3]:

    
print(np.unique(a))









    



[ 0 10 20 30]



In [4]:

    
print(type(np.unique(a)))









    



<class 'numpy.ndarray'>



In [5]:

    
l = [0, 0, 30, 10, 10, 20]
print(l)









    



[0, 0, 30, 10, 10, 20]



In [6]:

    
print(np.unique(l))









    



[ 0 10 20 30]



In [7]:

    
print(type(np.unique(l)))









    



<class 'numpy.ndarray'>



In [8]:

    
print(np.unique(a).size)



In [9]:

    
print(len(np.unique(a)))



In [10]:

    
u, counts = np.unique(a, return_counts=True)
print(u)









    



[ 0 10 20 30]



In [11]:

    
print(counts)



In [12]:

    
print(u[counts == 1])



In [13]:

    
print(u[counts != 1])



In [14]:

    
print(np.unique(a, return_counts=True))









    



(array([ 0, 10, 20, 30]), array([2, 2, 1, 1]))



In [15]:

    
print(type(np.unique(a, return_counts=True)))









    



<class 'tuple'>



In [16]:

    
u, indices = np.unique(a, return_index=True)
print(u)









    



[ 0 10 20 30]



In [17]:

    
print(indices)



In [18]:

    
print(a)









    



[ 0  0 30 10 10 20]



In [19]:

    
print(a[indices])









    



[ 0 10 20 30]



In [20]:

    
u, inverse = np.unique(a, return_inverse=True)
print(u)









    



[ 0 10 20 30]



In [21]:

    
print(inverse)









    



[0 0 3 1 1 2]



In [22]:

    
print(a)









    



[ 0  0 30 10 10 20]



In [23]:

    
print(u[inverse])









    



[ 0  0 30 10 10 20]



In [24]:

    
u, indices, inverse, counts = np.unique(a, return_index=True, return_inverse=True, return_counts=True)
print(u)









    



[ 0 10 20 30]



In [25]:

    
print(indices)



In [26]:

    
print(inverse)









    



[0 0 3 1 1 2]



In [27]:

    
print(counts)



In [28]:

    
print(np.unique(a, return_counts=True, return_index=True, return_inverse=True))









    



(array([ 0, 10, 20, 30]), array([0, 3, 5, 2]), array([0, 0, 3, 1, 1, 2]), array([2, 2, 1, 1]))



In [29]:

    
a_2d = np.array([[20, 20, 10, 10], [0, 0, 10, 30], [20, 20, 10, 10]])
print(a_2d)









    



[[20 20 10 10]
 [ 0  0 10 30]
 [20 20 10 10]]



In [30]:

    
print(np.unique(a_2d))









    



[ 0 10 20 30]



In [31]:

    
print(np.unique(a_2d, axis=0))









    



[[ 0  0 10 30]
 [20 20 10 10]]



In [32]:

    
print(np.unique(a_2d, axis=1))









    



[[10 10 20]
 [10 30  0]
 [10 10 20]]



In [33]:

    
print(a_2d[0])









    



[20 20 10 10]



In [34]:

    
print(np.unique(a_2d[0]))



In [35]:

    
print(a_2d[:, 2])



In [36]:

    
print(np.unique(a_2d[:, 2]))



In [37]:

    
print([np.unique(row) for row in a_2d])









    



[array([10, 20]), array([ 0, 10, 30]), array([10, 20])]



In [38]:

    
print([np.unique(row).tolist() for row in a_2d])









    



[[10, 20], [0, 10, 30], [10, 20]]



In [39]:

    
print([np.unique(row).size for row in a_2d])









    



[2, 3, 2]



In [40]:

    
print(a_2d.T)









    



[[20  0 20]
 [20  0 20]
 [10 10 10]
 [10 30 10]]



In [41]:

    
print([np.unique(row) for row in a_2d.T])









    



[array([ 0, 20]), array([ 0, 20]), array([10]), array([10, 30])]



In [42]:

    
print(a_2d.shape)









    



(3, 4)



In [43]:

    
print([np.unique(a_2d[:, i]) for i in range(a_2d.shape[1])])









    



[array([ 0, 20]), array([ 0, 20]), array([10]), array([10, 30])]



In [44]:

    
u, indices, inverse, counts = np.unique(a_2d, return_index=True, return_inverse=True, return_counts=True)
print(u)









    



[ 0 10 20 30]



In [45]:

    
print(indices)



In [46]:

    
print(a_2d.flatten())









    



[20 20 10 10  0  0 10 30 20 20 10 10]



In [47]:

    
print(a_2d.flatten()[indices])









    



[ 0 10 20 30]



In [48]:

    
print(inverse)









    



[2 2 1 1 0 0 1 3 2 2 1 1]



In [49]:

    
print(u[inverse])









    



[20 20 10 10  0  0 10 30 20 20 10 10]



In [50]:

    
print(u[inverse].reshape(a_2d.shape))









    



[[20 20 10 10]
 [ 0  0 10 30]
 [20 20 10 10]]



In [51]:

    
print(counts)



In [52]:

    
u, indices, inverse, counts = np.unique(a_2d, axis=0, return_index=True, return_inverse=True, return_counts=True)
print(u)









    



[[ 0  0 10 30]
 [20 20 10 10]]



In [53]:

    
print(indices)



In [54]:

    
print(a_2d[indices])









    



[[ 0  0 10 30]
 [20 20 10 10]]



In [55]:

    
print(inverse)



In [56]:

    
print(u[inverse])









    



[[20 20 10 10]
 [ 0  0 10 30]
 [20 20 10 10]]



In [57]:

    
print(counts)



In [58]:

    
print(a_2d)









    



[[20 20 10 10]
 [ 0  0 10 30]
 [20 20 10 10]]



In [59]:

    
u, indices = np.unique(a_2d, return_index=True)
print(u)









    



[ 0 10 20 30]



In [60]:

    
print(a_2d.flatten())









    



[20 20 10 10  0  0 10 30 20 20 10 10]



In [61]:

    
print(indices)



In [62]:

    
print(list(zip(*np.where(a_2d == 0))))









    



[(1, 0), (1, 1)]



In [63]:

    
d = {u: list(zip(*np.where(a_2d == u))) for u in np.unique(a_2d)}
print(d)









    



{0: [(1, 0), (1, 1)], 10: [(0, 2), (0, 3), (1, 2), (2, 2), (2, 3)], 20: [(0, 0), (0, 1), (2, 0), (2, 1)], 30: [(1, 3)]}



In [64]:

    
print(d[0])









    



[(1, 0), (1, 1)]



In [65]:

    
print(d[10])









    



[(0, 2), (0, 3), (1, 2), (2, 2), (2, 3)]



In [66]:

    
print(d[20])









    



[(0, 0), (0, 1), (2, 0), (2, 1)]



In [67]:

    
print(d[30])









    



[(1, 3)]



In [68]:

    
d = {u: list(zip(*np.where(a_2d == u)))
     for u, c in zip(*np.unique(a_2d, return_counts=True)) if c == 1}
print(d)









    



{30: [(1, 3)]}



In [69]:

    
d = {u: list(zip(*np.where(a_2d == u)))
     for u, c in zip(*np.unique(a_2d, return_counts=True)) if c <= 2}
print(d)









    



{0: [(1, 0), (1, 1)], 30: [(1, 3)]}