In [17]:

    

import numpy as np
X = np.arange(100).reshape((10,10))
X


    

    
Out[17]:





array([[ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9],
       [10, 11, 12, 13, 14, 15, 16, 17, 18, 19],
       [20, 21, 22, 23, 24, 25, 26, 27, 28, 29],
       [30, 31, 32, 33, 34, 35, 36, 37, 38, 39],
       [40, 41, 42, 43, 44, 45, 46, 47, 48, 49],
       [50, 51, 52, 53, 54, 55, 56, 57, 58, 59],
       [60, 61, 62, 63, 64, 65, 66, 67, 68, 69],
       [70, 71, 72, 73, 74, 75, 76, 77, 78, 79],
       [80, 81, 82, 83, 84, 85, 86, 87, 88, 89],
       [90, 91, 92, 93, 94, 95, 96, 97, 98, 99]])

In [18]:

    

x = X[np.array([2]),:]
x


    

    
Out[18]:





array([[20, 21, 22, 23, 24, 25, 26, 27, 28, 29]])

In [22]:

    

X[:,5] = X[:,5] * 100
X[:,5]


    

    
Out[22]:





array([ 10000,  30000,  50000,  70000,  90000, 110000, 130000, 150000,
       170000, 190000])

In [23]:

    

x


    

    
Out[23]:





array([[20, 21, 22, 23, 24, 25, 26, 27, 28, 29]])

In [24]:

    

X.ix_


    

    




---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-24-8f70c88ac4bb> in <module>()
----> 1 X.ix_

AttributeError: 'numpy.ndarray' object has no attribute 'ix_'

In [24]:

    

X = np.array([[]])
X.shape


    

In [ ]:

    

# X2 = np.column_stack([np.arange(100), np.arange(100) + 10])
X2.shape
np.arange(2)
X2[np.arange(10), :][:, np.arange(1)]