NumPy - Array From Existing Data

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In this chapter, we will discuss how to create an array from existing data.

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)

The constructor takes the following parameters.

The following examples show how you can use the asarray function.

Example 1

# convert list to ndarray 
import numpy as np 

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

Its output would be as follows −

[1  2  3] 

Example 2

# dtype is set 
import numpy as np 

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

Now, the output would be as follows −

[ 1.  2.  3.] 

Example 3

# ndarray from tuple 
import numpy as np 

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

Its output would be −

[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

Here, the output would be as follows −

[(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)

The constructor takes the following parameters.

Example

The following examples demonstrate the use of frombuffer function.

import numpy as np 
s = 'Hello World' 
a = np.frombuffer(s, dtype = 'S1') 
print a

Here is its output −

['H'  'e'  'l'  'l'  'o'  ' '  'W'  'o'  'r'  'l'  'd']

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)

Here, the constructor takes the following parameters.

The following examples show how to use the built-in range() function to return a list object. An iterator of this list is used to form an ndarray object.

Example 1

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

Its output is as follows −

[0,  1,  2,  3,  4]

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

Now, the output would be as follows −

[0.   1.   2.   3.   4.]