Append/concatenate Numpy array to Numpy array

Question

I have two np arrays, one is 1 dimensional, and the other it between 0 and 8 dimensional. I'm trying to append the multidimensional array onto the other array, as you would with a list. I've tried np.append(1dim, multidim) and np.concatenate([1dim, multidim]) but neither have worked.

[-33.752, 150.902, 38.022, 203.0, 1.0]

[[ -33.75   150.9     39.805    0.       1.   ]
 [ -33.75   150.902   44.697    1.       1.   ]
 [ -33.75   150.905   49.054    2.       1.   ]
 [ -33.752  150.905   39.062  204.       1.   ]
 [ -33.755  150.905   40.698  406.       1.   ]
 [ -33.755  150.902   37.512  405.       1.   ]
 [ -33.755  150.9     36.249  404.       1.   ]
 [ -33.752  150.9     36.627  202.       1.   ]]

to become:

[-33.752, 150.902, 38.022, 203.0, 1.0],
 [ -33.75   150.9     39.805    0.       1.   ]
 [ -33.75   150.902   44.697    1.       1.   ]
 [ -33.75   150.905   49.054    2.       1.   ]
 [ -33.752  150.905   39.062  204.       1.   ]
 [ -33.755  150.905   40.698  406.       1.   ]
 [ -33.755  150.902   37.512  405.       1.   ]
 [ -33.755  150.9     36.249  404.       1.   ]
 [ -33.752  150.9     36.627  202.       1.   ]]

I would like to be able to reference the multidim array by using 1dim[1]

Answer 1

Your example output shows a (1x8) array concatenated with an (Nx8) array to form an (N+1 x 8) array.

If you want to create a "thing" where the first element is the 1-D array and the second element is the N-D array, a list or tuple is your bet. Numpy doesn't really have a great facility for this.

If you want to create an array that is the combination of the two 2D, based on your example, np.vstack([flat_array, big_array]) will do that.

By the way, when describing the number of dimensions something has, array.ndim is the same as len(array.shape). Note that an array with 5 rows and 8 columns is two dimensional in the context of numpy.

Answer 2

You have to use numpy.append or numpy.concatenate. But careful about the shape of your array. For your case you have to define the correct shape

ans=np.append([[small array]],[big array], axis=0) (Note that the extra [] is for correct shape, read the numpy.append tutorial)

Answer 3

Or you can do it manually for any shape

blank= [ ] #create a blank list
a=1D array
blank.append(a)
b=nD array
for i in range(len(b)):
     blank.append(b[i])
answer=np.array(blank)