# Add|Append elements to Numpy array in Python(3 methods)

In this post, we are going to learn about how to add|append elements to NumPy array in Python. by using append(), insert(), concatenate() function with help of python program examples3 Methods to Add elements to Numpy array in Python

• Numpy.append()
• Numpy.insert()
• Numpy.concatenate()

### 1. add| append element to Numpy array using append()

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

#### Syntax

```numpy.append(arr,values,axis=none)
```

#### 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.

#### Python Program to add element to NumPy array Using append()

```import numpy as np

myarr = np.array([12,14,700,60,50])
numarr = np.array([3,6,9])

#append an element at end of array

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

#append array at end of array

resarr = np.append(myarr,numarr)
print('\n appended an Array in Numpy array: ', resarr)

```

Output

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

appended an Array in Numpy array :  [ 12  14 700  60  50   3   6   9]
```

### 2. add| append element to Numpy array using insert()

The numpy library insert() function adds values in the numpy array along with the axis before the given index.

#### Syntax

```numpy.insert(arr,obj,values,axis=none)
```

#### Parameters

• arr: The copy of the array in which values are to be appended.
• obj :objects define index or indices before values inserted.
• 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.

#### Python Program to add element to NumPy array Using append()

```import numpy as np
arr = np.array([[10,12],[23,24],[15,16]])

print ('The original array is flattened before insert.when axis is not passed')
result_arr = np.insert(arr,2,[30,33])

print(result_arr)

print ('\n The axis 0: is passed:')
print (np.insert(arr,1,,axis = 0))

print ('\n The axis 1: is passed:\n')
print (np.insert(arr,1,56,axis = 1))

```

Output

```The original array is flattened before insert.when axis is not passed
[10 12 30 33 23 24 15 16]

The axis 0: is passed:
[[10 12]
[45 45]
[23 24]
[15 16]]

The axis 1: is passed:

[[10 56 12]
[23 56 24]
[15 56 16]]
```

### 3.add|append element to Numpy array using concatenate()

The NumPy array concatenate() function concate two numpy array of same shape either row-wise or column-wise.This function by default concatenate arrays row-wise (axis=0).

#### Syntax

```numpy.concatenate((a1, a2, ...an), axis=0, out=None, dtype=None)
```

#### Parameters

• a1..an : The sequence of array_like object.The sequence must be of same shape
• axis :The axis along which array is joined.It is optional parameter.
• axis=none: The input array is flatten before use.
• axis =1: The array is join column-wise
• axis = 0 : The array is joined row-wise.It is defulat value of axis.
• Out : optional The output ndarray if provided output is placed in this array.The shape must be correct.
• dtype : optional if provided the output array of this type or str.

#### Python program to Add|append to Numpy array using concatenate()

```import numpy as np

nparr1 = np.array([13, 14, 15, 18, 20])

nparr2 = np.array([22, 32, 33, 34, 36])

joined_nparr = np.concatenate( (nparr1, nparr2) )
print(joined_nparr)

```

Output

```[13 14 15 18 20 22 32 33 34 36]
```

#### Python program to add|append 2D Numpy array using concatenate()

```import numpy as np

nparr1 = np.array([[13, 14, 15],
[26, 12, 23],
[24, 25, 30]])

nparr2 = np.array([ [11, 54, 9],
[3, 6, 7],
[4, 8, 62]])
# Concatenate 2D np Arrays column wise
joined_nparr = np.concatenate( (nparr1, nparr2), axis=1 )

# Concatenate 2D np Arrays row-wise
join_nparr_rowwise = np.concatenate( (nparr1, nparr2), axis=0 )

print('concatenate column-wise:\n',joined_nparr)
print('\n concatenate row-wise:',join_nparr_rowwise)
```

Output

```concatenate column-wise:
[[13 14 15 11 54  9]
[26 12 23  3  6  7]
[24 25 30  4  8 62]]

concatenate row-wise: [[13 14 15]
[26 12 23]
[24 25 30]
[11 54  9]
[ 3  6  7]
[ 4  8 62]]
```

### Summary

In this post, we have learned how to Add|Append elements to the Numpy array in Python with examples.