Updated On : Jun-27,2020 Time Investment : ~10 mins

# Learning Numpy - Simple Tutorial For Beginners - NumPy - Array From Existing Data Part 6¶

### numpy.asarray¶

This function is similar to numpy.array except for the fact that it has fewer parameters. This routine is useful for converting Python sequence into ndarray.

```numpy.asarray(a, dtype = None, order = None)
```
Parameter Description
a Input data in any form such as list, list of tuples, tuples, tuple of tuples or tuple of lists
Dtype By default, the data type of input data is applied to the resultant ndarray
Order C (row major) or F (column major). C is default

### Example 1¶

```# convert list to ndarray
import numpy as np

x = [1,2,3]
a = np.asarray(x)
print (a)
```
```[1 2 3]
```

### Example 2¶

```# dtype is set
import numpy as np

x = [1,2,3]
a = np.asarray(x, dtype = float)
print (a)
```
```[1. 2. 3.]
```

### Example 3¶

```# ndarray from tuple
import numpy as np

x = (1,2,3)
a = np.asarray(x)
print (a)
```
```[1 2 3]
```

### Example 4¶

```# ndarray from list of tuples
import numpy as np

x = [(1,2,3),(4,5)]
a = np.asarray(x)
print (a)
```
```[(1, 2, 3) (4, 5)]
```

### numpy.frombuffer¶

This function interprets a buffer as one-dimensional array. Any object that exposes the buffer interface is used as parameter to return an ndarray.

```numpy.frombuffer(buffer, dtype = float, count = -1, offset = 0)
```
Parameter Description
buffer Any object that exposes buffer interface
dtype Data type of returned ndarray. Defaults to float
count The number of items to read, default -1 means all data
offset The starting position to read from. Default is 0

### numpy.fromiter¶

This function builds an ndarray object from any iterable object. A new one-dimensional array is returned by this function.

```numpy.fromiter(iterable, dtype, count = -1)
```
Parameter Description
iterable Any iterable object
dtype Data type of resultant array
count The number of items to be read from iterator. Default is -1 which means all data to be read

### Example 1¶

```# create list object using range function
import numpy as np
list = range(5)
print (list)
```
```range(0, 5)
```

### Example 2¶

```# obtain iterator object from list
import numpy as np
list = range(5)
it = iter(list)

# use iterator to create ndarray
x = np.fromiter(it, dtype = float)
print (x)
```
```[0. 1. 2. 3. 4.]
```
Dolly Solanki

## Comfortable Learning through Video Tutorials?

If you are more comfortable learning through video tutorials then we would recommend that you subscribe to our YouTube channel.

## Stuck Somewhere? Need Help with Coding? Have Doubts About the Topic/Code?

When going through coding examples, it's quite common to have doubts and errors.

If you have doubts about some code examples or are stuck somewhere when trying our code, send us an email at coderzcolumn07@gmail.com. We'll help you or point you in the direction where you can find a solution to your problem.

You can even send us a mail if you are trying something new and need guidance regarding coding. We'll try to respond as soon as possible.

## Want to Share Your Views? Have Any Suggestions?

If you want to

• provide some suggestions on topic