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 |

In [1]:

```
# convert list to ndarray
import numpy as np
x = [1,2,3]
a = np.asarray(x)
print (a)
```

In [1]:

```
# dtype is set
import numpy as np
x = [1,2,3]
a = np.asarray(x, dtype = float)
print (a)
```

In [3]:

```
# ndarray from tuple
import numpy as np
x = (1,2,3)
a = np.asarray(x)
print (a)
```

In [4]:

```
# ndarray from list of tuples
import numpy as np
x = [(1,2,3),(4,5)]
a = np.asarray(x)
print (a)
```

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 |

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 |

In [11]:

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

In [12]:

```
# 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)
```

Dolly Solanki

argparse - Simple Guide to Command-Line Arguments Handling in Python

traceback - How to Extract, Format, and Print Error Stack Traces in Python

How to Display Contents of Different Types in Jupyter Notebook/Lab?

List of Useful Magic Commands in Jupyter Notebook/Lab