# Combining a one and a two-dimensional NumPy Array

Sometimes we need to combine 1-D and 2-D arrays and display their elements. Numpy has a function named as numpy.nditer(), which provides this facility.

Syntax: numpy.nditer(op, flags=None, op_flags=None, op_dtypes=None, order=’K’, casting=’safe’, op_axes=None, itershape=None, buffersize=0)

Example 1:

## Python3

 `# importing Numpy package  ``import` `numpy as np `` ` `num_1d ``=` `np.arange(``5``) ``print``(``"One dimensional array:"``) ``print``(num_1d) `` ` `num_2d ``=` `np.arange(``10``).reshape(``2``,``5``) ``print``(``"\nTwo dimensional array:"``) ``print``(num_2d) `` ` `# Combine 1-D and 2-D arrays and display  ``# their elements using numpy.nditer()  ``for` `a, b ``in` `np.nditer([num_1d, num_2d]): ``    ``print``(``"%d:%d"` `%` `(a, b),)`

Output:

```One dimensional array:
[0 1 2 3 4]

Two dimensional array:
[[0 1 2 3 4]
[5 6 7 8 9]]
0:0
1:1
2:2
3:3
4:4
0:5
1:6
2:7
3:8
4:9
```

Example 2:

## Python3

 `# importing Numpy package  ``import` `numpy as np `` ` `num_1d ``=` `np.arange(``7``) ``print``(``"One dimensional array:"``) ``print``(num_1d) `` ` `num_2d ``=` `np.arange(``21``).reshape(``3``,``7``) ``print``(``"\nTwo dimensional array:"``) ``print``(num_2d) `` ` `# Combine 1-D and 2-D arrays and display  ``# their elements using numpy.nditer()  ``for` `a, b ``in` `np.nditer([num_1d, num_2d]): ``    ``print``(``"%d:%d"` `%` `(a, b),)`

Output:

```One dimensional array:
[0 1 2 3 4 5 6]

Two dimensional array:
[[ 0  1  2  3  4  5  6]
[ 7  8  9 10 11 12 13]
[14 15 16 17 18 19 20]]
0:0
1:1
2:2
3:3
4:4
5:5
6:6
0:7
1:8
2:9
3:10
4:11
5:12
6:13
0:14
1:15
2:16
3:17
4:18
5:19
6:20
```

Example 3:

## Python3

 `# importing Numpy package  ``import` `numpy as np `` ` `num_1d ``=` `np.arange(``2``) ``print``(``"One dimensional array:"``) ``print``(num_1d) `` ` `num_2d ``=` `np.arange(``12``).reshape(``6``,``2``) ``print``(``"\nTwo dimensional array:"``) ``print``(num_2d) `` ` `# Combine 1-D and 2-D arrays and display ``# their elements using numpy.nditer()  ``for` `a, b ``in` `np.nditer([num_1d, num_2d]): ``    ``print``(``"%d:%d"` `%` `(a, b),)`

Output:

```One dimensional array:
[0 1]

Two dimensional array:
[[ 0  1]
[ 2  3]
[ 4  5]
[ 6  7]
[ 8  9]
[10 11]]
0:0
1:1
0:2
1:3
0:4
1:5
0:6
1:7
0:8
1:9
0:10
1:11
```

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