# NumPy ones – A Complete Guide Hello and welcome to this tutorial on Numpy ones. In this tutorial, we will be learning about the NumPy ones() method and also seeing a lot of examples regarding the same. So let us begin!

## What is the NumPy ones method?

NumPy `ones` returns a Numpy array of the given shape and data type with all values set to 1.

## Syntax of NumPy ones

Let us first have a look at the syntax of NumPy ones.

```numpy.ones(shape, dtype=None, order='C', like=None)
```

Returns:
An array with the given shape, data type and order filled with only ones.

## Examples of using NumPy ones

Let’s now look at some practical examples of the `numpy.ones()` method.

### 1-dimensional array using ones

```import numpy as np

one_dim_array = np.ones(4)
print(one_dim_array)
```

Output:

```[1. 1. 1. 1.]
```

### 2-dimensional array using zeros

N x M array

```import numpy as np

two_dim_array = np.ones((4, 2))
print(two_dim_array)
```

Output:

```[[1. 1.]
[1. 1.]
[1. 1.]
[1. 1.]]
```

1 x N array

```import numpy as np

one_row_array = np.ones((1, 3))
print(one_row_array)
```

Output:

```[[1. 1. 1.]]
```

N x 1 array

```import numpy as np

one_col_array = np.ones((5, 1))
print(one_col_array)
```

Output:

```[[1.]
[1.]
[1.]
[1.]
[1.]]
```

### 1-dimensional int-type array

```import numpy as np

one_dim_int_array = np.ones(5, dtype=np.int64)
print(one_dim_int_array)
```

Output:

```[1 1 1 1 1]
```

### 2-dimensional int-type array

```import numpy as np

two_dim_int_array = np.ones((3, 3), dtype=np.int64)
print(two_dim_int_array)
```

Output:

```[[1 1 1]
[1 1 1]
[1 1 1]]
```

### 1-dimensional custom data type array

```import numpy as np

custom_one_dim_array = np.ones(4, dtype=[('x', 'int'), ('y', 'float')])
print(custom_one_dim_array)
print(custom_one_dim_array.dtype)
```

Output:

```[(1, 1.) (1, 1.) (1, 1.) (1, 1.)]
[('x', '<i4'), ('y', '<f8')]
```

In this example, we specified the first value as an int and the second as a float.

### 2-dimensional custom data type array

We can specify the elements of the array as a tuple and also specify their data types.

```import numpy as np

custom_two_dim_array = np.ones((2, 3), dtype=[('x', 'float'), ('y', 'int')])
print(custom_two_dim_array)
print(custom_two_dim_array.dtype)
```

Output:

```[[(1., 1) (1., 1) (1., 1)]
[(1., 1) (1., 1) (1., 1)]]
[('x', '<f8'), ('y', '<i4')]
```

Here, the code specifies the first value of the tuple in the array elements to be a float and the second one to be an int.

## Conclusion

That’s all! In this tutorial, we learned about the Numpy ones method and practiced different types of examples using the same.