How do i add elements to a row in a matrix in python?

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 3
4 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]])

Given a Numpy array, the task is to add rows/columns basis on requirements to the Numpy array. Let’s see a few examples of this problem in Python.

Add columns in the Numpy array

Method 1: Using np.append()

Python3

import numpy as np

ini_array = np.array([[1, 2, 3], [45, 4, 7], [9, 6, 10]])

print("initial_array : ", str(ini_array));

column_to_be_added = np.array([[1], [2], [3]])

arr = np.append(ini_array, column_to_be_added, axis=1)

print ("resultant array", str(result))

Output:

initial_array :  [[ 1  2  3]
 [45  4  7]
 [ 9  6 10]]
resultant array [[ 1  2  3  1]
 [45  4  7  2]
 [ 9  6 10  3]]

Method 2: Using np.concatenate

Python3

import numpy as np

ini_array = np.array([[1, 2, 3], [45, 4, 7], [9, 6, 10]])

column_to_be_added = np.array([[1], [2], [3]])

arr = np.concatenate([ini_array, column_to_be_added], axis=1)

print ("resultant array", str(result))

Output:

resultant array [[ 1  2  3  1]
 [45  4  7  2]
 [ 9  6 10  3]]

Method 3: Using np.insert()

Python3

import numpy as np

ini_array = np.array([[1, 2, 3], [45, 4, 7], [9, 6, 10]])

column_to_be_added = np.array([[1], [2], [3]])

arr = np.insert(ini_array, 0, column_to_be_added, axis=1)

print ("resultant array", str(result))

Output:

resultant array [[ 1  2  3  1]
 [45  4  7  2]
 [ 9  6 10  3]]

Method 4: Using np.hstack()  

Python3

import numpy as np

ini_array = np.array([[1, 2, 3], [45, 4, 7], [9, 6, 10]])

column_to_be_added = np.array([1, 2, 3])

result = np.hstack((ini_array, np.atleast_2d(column_to_be_added).T))

print ("resultant array", str(result))

Output:

resultant array [[ 1  2  3  1]
 [45  4  7  2]
 [ 9  6 10  3]]

Method 5: Using np.column_stack() 

Python3

import numpy as np

ini_array = np.array([[1, 2, 3], [45, 4, 7], [9, 6, 10]])

column_to_be_added = np.array([1, 2, 3])

result = np.column_stack((ini_array, column_to_be_added))

print ("resultant array", str(result))

Output: 

resultant array [[ 1  2  3  1]
 [45  4  7  2]
 [ 9  6 10  3]]

Add row in Numpy array

Method 1: Using np.r_ 

Python3

import numpy as np

ini_array = np.array([[1, 2, 3], [45, 4, 7], [9, 6, 10]])

print("initial_array : ", str(ini_array));

row_to_be_added = np.array([1, 2, 3])

result = np.r_[ini_array,[row_to_be_added]]

print ("resultant array", str(result))

Output:

initial_array :  [[ 1  2  3]
 [45  4  7]
 [ 9  6 10]]

resultant array [[ 1  2  3]
 [45  4  7]
 [ 9  6 10]
 [ 1  2  3]]

Method 2: Using np.insert 

Python3

import numpy as np

ini_array = np.array([[1, 2, 3], [45, 4, 7], [9, 6, 10]])

row_to_be_added = np.array([1, 2, 3])

row_n = arr.shape[0]

arr = np.insert(ini_array,row_n,[row_to_be_added],axis= 0)

print ("resultant array", str(result))

Output:

resultant array [[ 1  2  3]
 [45  4  7]
 [ 9  6 10]
 [ 1  2  3]]

Method 3: Using np.vstack() 

Python3

import numpy as np

ini_array = np.array([[1, 2, 3], [45, 4, 7], [9, 6, 10]])

row_to_be_added = np.array([1, 2, 3])

result = np.vstack ((ini_array, row_to_be_added) )

print ("resultant array", str(result))

Output:

resultant array [[ 1  2  3]
 [45  4  7]
 [ 9  6 10]
 [ 1  2  3]]

Method 4: Using numpy.append()

Sometimes we have an empty array and we need to append rows in it. Numpy provides the function to append a row to an empty Numpy array using numpy.append() function.

Example 1: Adding new rows to an empty 2-D array

Python3

import numpy as np  

empt_array = np.empty((0,2), int)

print("Empty array:")

print(empt_array)

empt_array = np.append(empt_array, np.array([[10,20]]), axis=0)

empt_array = np.append(empt_array, np.array([[40,50]]), axis=0)

print("\nNow array is:")

print(empt_array)

Empty array:
[]

Now array is:
[[10 20]
[40 50]]

Example 2: Adding new rows to an empty 3-D array

Python3

import numpy as np  

empt_array = np.empty((0,3), int)

print("Empty array:")

print(empt_array)

empt_array = np.append(empt_array, np.array([[10,20,40]]), axis=0)

empt_array = np.append(empt_array, np.array([[40,50,55]]), axis=0)

empt_array = np.append(empt_array, np.array([[40,50,55]]), axis=0)

print("\nNow array is:")

print(empt_array)

Empty array:
[]

Now array is:
[[10 20 40]
 [40 50 55]
 [40 50 55]]

Example 3: Adding new rows to an empty 4-D array

Python3

import numpy as np  

empt_array = np.empty((0,4), int)

print("Empty array:")

print(empt_array)

empt_array = np.append(empt_array, np.array([[100,200,400,888]]), axis=0)

empt_array = np.append(empt_array, np.array([[405,500,550,558]]), axis=0)

empt_array = np.append(empt_array, np.array([[404,505,555,145]]), axis=0)

empt_array = np.append(empt_array, np.array([[44,55,550,150]]), axis=0)

print("\nNow array is:")

print(empt_array)

Empty array:
[]

Now array is:
[[100 200 400 888]
 [405 500 550 558]
 [404 505 555 145]
 [ 44  55 550 150]]

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