I am trying to concatenate two arrays: a and b, where
a.shape
(1460,10)
b.shape
(1460,)
I tried using hstack and concatenate as:
np.hstack((a,b))
c=np.concatenate(a,b,0)
I am stuck with the error
ValueError: all the input arrays must have same number of dimensions
Please guide me for concatenation and generating array c with dimensions 1460 x 11.
Try
b = np.expand_dims( b,axis=1 )
then
np.hstack((a,b))
or
np.concatenate( (a,b) , axis=1)
will work properly.
np.c_[a, b] concatenates along the last axis.
Per the docs,
... arrays will be stacked along their last axis after being upgraded to at least 2-D with 1's post-pended to the shape
Since b has shape (1460,) its shape gets upgraded to (1460, 1) before concatenation along the last axis.
In [26]: c = np.c_[a,b]
In [27]: c.shape
Out[27]: (1460, 11)
np.c_ is followed by brackets [...] rather than paretheses (...). The error 'CClass' object is not callable is saying that np.c_ can not be called, which is what happens when it is followed by parentheses.The most basic operation that works is:
np.concatenate((a,b[:,None]),axis=1)
The [:,None] bit turns b into a (1060,1) array. Now the 1st dimensions of both arrays match, and you can easily concatenate on the 2nd.
There a many ways of adding the 2nd dimension to b, such as reshape and expanddims. hstack uses atleast_1d which does not help in this case. atleast_2d adds the None on the wrong side. I strongly advocate learning the [:,None] syntax.
Once the arrays are both 2d and match on the correct dimensions, concatenation is easy.
