The `numpy.asarray()`

function in Numpy is used to convert** the input or any existing data into an array**.

- The existing data can be in the form of
**Lists, Tuples, tuples of tuples, list of tuples, tuples of lists, etc**. - In case if you want to convert any
**python sequence into the Numpy array object**i.e ndarray then this function is helpful for you.

### Syntax of `numpy.asarray()`

:

Given below is the basic syntax to use this function:

`numpy.asarray(sequence, dtype, order) `

**Parameters:**

Let us discuss the parameters mentioned above for the `asarray()`

function:

**sequence**

This parameter is used to indicate the input data that can be in any form and is to be converted into an array. This parameter includes lists, lists of tuples, tuples, tuples of tuples, tuples of lists and ndarrays.**dtype**

This parameter is used to indicate the data type of each item of the array. It is an**optional**parameter with default value**None**.**order**

This parameter is used to indicate the memory representation that is whether to use row-major (C-style) or column-major (Fortran-style) The default value is set to**‘C’**.

**Returned Values:**

This function will **return an array** with all the values from the sequence used to create the array. If the input is already an ndarray with matching `dtype`

and **order** then this function will not create any copy.

Now it’s time to take a look at some examples of this function.

## Example 1:

In the code snippet given below we will convert a Python list into an array:

```
import numpy as np
mylist = [1, 2,4,5,8,10]
np.asarray(mylist)
```

Output:

array([ 1, 2, 4, 5, 8, 10])

## Example 2:

In the code snippet below we will create a NumPy array from a Python tuple:

```
import numpy as np
inp = (10,9,1,2,3,4,5,6,7,8)
a = np.asarray(inp);
print("The output is:")
print(a)
print("The datatype of output is:")
print(type(a))
```

Output:

The output is:

[10 9 1 2 3 4 5 6 7 8]

The datatype of output is:

<class 'numpy.ndarray'>

## Example 3:

In the code snippet given below we will create an array using more than one list:

```
import numpy as np
l = [[1,2,3,4,5,6,7],[8,9],[12,34,45]]
a = np.asarray(l);
print("The data type of output is:")
print(type(a))
print("The output array is:")
print(a)
```

Output:

The data type of output is:

<class 'numpy.ndarray'>

The output array is:

[list([1, 2, 3, 4, 5, 6, 7]) list([8, 9]) list([12, 34, 45])]