You can use the following syntax to add a row to a matrix in NumPy:

#add new_row to current_matrix current_matrix = np.vstack([current_matrix, new_row])

You can also use the following syntax to only add rows to a matrix that meet a certain condition:

#only add rows where first element is less than 10 current_matrix = np.vstack((current_matrix, new_rows[new_rows[:,0] < 10]))

The following examples shows how to use this syntax in practice.

**Example 1: Add Row to Matrix in NumPy**

The following code shows how to add a new row to a matrix in NumPy:

**import numpy as np
#define matrix
current_matrix = np.array([[1 ,2 ,3], [4, 5, 6], [7, 8, 9]])
#define row to add
new_row = np.array([10, 11, 12])
#add new row to matrix
current_matrix = np.vstack([current_matrix, new_row])
#view updated matrix
current_matrix
array([[ 1, 2, 3],
[ 4, 5, 6],
[ 7, 8, 9],
[10, 11, 12]])
**

Notice that the last row has been successfully added to the matrix.

**Example 2: Add Rows to Matrix Based on Condition**

The following code shows how to add several new rows to an existing matrix based on a specific condition:

import numpy as np #define matrix current_matrix = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) #define potential new rows to add new_rows = np.array([[6, 8, 10], [8, 10, 12], [10, 12, 14]]) #only add rows where first element in row is less than 10 current_matrix = np.vstack((current_matrix, new_rows[new_rows[:,0] < 10])) #view updated matrix current_matrix array([[ 1, 2, 3], [ 4, 5, 6], [ 7, 8, 9], [ 6, 8, 10], [ 8, 10, 12]])

Only the rows where the first element in the row was less than 10 were added.

**Note**: You can find the complete online documentation for the **vstack()** function here.

**Additional Resources**

The following tutorials explain how to perform other common operations in NumPy:

How to Find Index of Value in NumPy Array

How to Add Numpy Array to Pandas DataFrame

How to Convert NumPy Array to Pandas DataFrame