Numpy - add row to array

well u can do this :

  newrow = [1,2,3]  A = numpy.vstack([A, newrow])

What is X? If it is a 2D-array, how can you then compare its row to a number: i < 3?

EDIT after OP's comment:

A = array([[0, 1, 2], [0, 2, 0]])X = array([[0, 1, 2], [1, 2, 0], [2, 1, 2], [3, 2, 0]])

add to A all rows from X where the first element < 3:

import numpy as npA = np.vstack((A, X[X[:,0] < 3]))# returns: array([[0, 1, 2],       [0, 2, 0],       [0, 1, 2],       [1, 2, 0],       [2, 1, 2]])

As this question is been 7 years before, in the latest version which I am using is numpy version 1.13, and python3, I am doing the same thing with adding a row to a matrix, remember to put a double bracket to the second argument, otherwise, it will raise dimension error.

In here I am adding on matrix A

1 2 34 5 6

with a row

7 8 9

same usage in np.r_

A = [[1, 2, 3], [4, 5, 6]]np.append(A, [[7, 8, 9]], axis=0)    >> array([[1, 2, 3],              [4, 5, 6],              [7, 8, 9]])#or np.r_[A,[[7,8,9]]]

Just to someone's intersted, if you would like to add a column,

array = np.c_[A,np.zeros(#A's row size)]

following what we did before on matrix A, adding a column to it

np.c_[A, [2,8]]>> array([[1, 2, 3, 2],          [4, 5, 6, 8]])

If you want to prepend, you can just flip the order of the arguments, i.e.:

np.r_([[7, 8, 9]], A)    >> array([[7, 8, 9],             [1, 2, 3],             [4, 5, 6]])