# How to extend NumPy array in Python

In this post, we are going to learn how to extend the NumPy array in Python. To extend elements to the NumPy array we pass the element or array that we want to extend to the NumPy array.

### Ways to extend NumPy array in Python

• Extend element to Numpy Array append().
• Extend NumPy array row-wise in Python.
• Extend NumPy array column-wise.
• Extend NumPy array with zeros.
• Extend NumPy array with same value.

### Numpy Array append()

The Numpy appends() function adds an element in a NumPy array at the end of the array. This method does not modify the original array else returns a copy of the array after adding the passed element or array.

#### Parameters

• arr: The copy of the array in which values are to be appended.
• values: The values adding or append to array.The shape(size) must be same as arr exclude axis.If axis is not passed the value can be any shape and flatten before use.
• axis: The axis represent adding values row-wise or columns-wise.if none both array or values are flatten before use.

### 1. Extend an element to NumPy array using append()

In this Python program, we have extended an element to the NumPy array by using the append() function. This is how we extend an element in the NumPy array.

#### Python Program to extend an element to NumPy array

```import numpy as np

myarr = np.array([12,14,700,60,50])
]

#extend an element at end of array

resarr = np.append(myarr, 90)
print('extend an element to Numpy array: ', resarr)

```

Output

```append an element to Numpy  array:  [ 12  14 700  60  50  90]

```

### 2. How to Extend NumPy array row-wise in Python

We have a two-dimensional numpy array and extend an array using numpy append() function row-wise bypassing axis =0.

• To use numpy function first need to import NumPy libraray “import numpy as np”
• The resarr is array after extended
• Printing the result array using print() method

#### Python Program to extend 2D NumP array row-wise

```import numpy as np

myarr = np.array([[12,14,700],[20,75,60]])

appendarr = [[15,16,17]]

#extend array to Numpy array

resarr = np.append(myarr, appendarr,axis=0)
print('extend element row-wise Numpy array: ', resarr)

```

Output

```extend element row-wise Numpy array:  [[ 12  14 700]
[ 20  75  60]
[ 15  16  17]]
```

### 3. Extend NumPy array column-wise in Python

In this Python program, We are extending a numpy array using append() function column-wise bypassing axis =1.

#### Python Program to extend 2D NumP array column-wise

```import numpy as np

myarr = [[15,16,17],[23,24,26]]

appendarr = [[12,14,700],[20,75,60]]

resarr = np.append(myarr, appendarr,axis=1)
print('extend element column-wise Numpy array: ', resarr)

```

Output

```extend element column-wise Numpy array:  [[ 15  16  17  12  14 700]
[ 23  24  26  20  75  60]]
```

### 4. Extend Numpy array with zeros

In this Python program, we are extending a 1D and 2D Numpy array with zeros by using the np.pad() function. This is how we extend the NumPy array with zeros.

#### Python Program to extend NumPy array with zeros

```import numpy as np

myarr = np.array([3,6,9])

#extend 1D NumPy  array

#extend 2D NumPy  array
myarr2D = np.array([[4,8],[12,16]]) # 2D array

```

Output

``` 2D zero extend array:
[[ 0  0  0  0  0  0]
[ 0  0  0  0  0  0]
[ 0  0  4  8  0  0]
[ 0  0 12 16  0  0]
[ 0  0  0  0  0  0]
[ 0  0  0  0  0  0]]
```

### 5. Extend NumPy array with same value

To extend the NumPy array with the same value. The numpy.full() function is used to create an array of a given shape that contains the same values. Let us understand with examples how to extend the NumPy array with the same values.

#### Python Program to extend NumPy array with same values

```import numpy as np
nparr = np.full((2,3), 6)
print(nparr)

```

Output

```[[6 6 6]
[6 6 6]]
```

### Summary

In this post we have learnt how to extend NumPy array in Python by usinh numpy.append(),numpy.pad() to extend with zero and nump.full() to extend with same values