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Append a NumPy array to a NumPy array

Posted by: admin November 29, 2017 Leave a comment

Questions:

I have a numpy_array. Something like [ a b c ].

And then I want to append it into another NumPy array (just like we create a list of lists). How do we create an array of NumPy arrays containing NumPy arrays?

I tried to do the following without any luck

>>> M = np.array([])
>>> M
array([], dtype=float64)
>>> M.append(a,axis=0)
Traceback (most recent call last):
 File "<stdin>", line 1, in <module>
AttributeError: 'numpy.ndarray' object has no attribute 'append'
>>> a
array([1, 2, 3])
Answers:
In [1]: import numpy as np

In [2]: a = np.array([[1, 2, 3], [4, 5, 6]])

In [3]: b = np.array([[9, 8, 7], [6, 5, 4]])

In [4]: np.concatenate((a, b))
Out[4]: 
array([[1, 2, 3],
       [4, 5, 6],
       [9, 8, 7],
       [6, 5, 4]])

or this:

In [1]: a = np.array([1, 2, 3])

In [2]: b = np.array([4, 5, 6])

In [3]: np.vstack((a, b))
Out[3]: 
array([[1, 2, 3],
       [4, 5, 6]])

Questions:
Answers:

Well, the error message says it all: NumPy arrays do not have an append() method. There’s a free function numpy.append() however:

numpy.append(M, a)

This will create a new array instead of mutating M in place. Note that using numpy.append() involves copying both arrays. You will get better performing code if you use fixed-sized NumPy arrays.

Questions:
Answers:

Sven said it all, just be very cautious because of automatic type adjustments when append is called.

In [2]: import numpy as np

In [3]: a = np.array([1,2,3])

In [4]: b = np.array([1.,2.,3.])

In [5]: c = np.array(['a','b','c'])

In [6]: np.append(a,b)
Out[6]: array([ 1.,  2.,  3.,  1.,  2.,  3.])

In [7]: a.dtype
Out[7]: dtype('int64')

In [8]: np.append(a,c)
Out[8]: 
array(['1', '2', '3', 'a', 'b', 'c'], 
      dtype='|S1')

As you see based on the contents the dtype went from int64 to float32, and then to S1

Questions:
Answers:

You may use numpy.append()

import numpy

B = numpy.array([3])
A = numpy.array([1, 2, 2])
B = numpy.append( B , A )

print B

> [3 1 2 2]

This will not create two separate arrays but will append two arrays into a single dimensional array.

Questions:
Answers:

Actually one can always create an ordinary list of numpy arrays and convert it later.

In [1]: import numpy as np

In [2]: a = np.array([[1,2],[3,4]])

In [3]: b = np.array([[1,2],[3,4]])

In [4]: l = [a]

In [5]: l.append(b)

In [6]: l = np.array(l)

In [7]: l.shape
Out[7]: (2, 2, 2)

In [8]: l
Out[8]: 
array([[[1, 2],
        [3, 4]],

       [[1, 2],
        [3, 4]]])

Questions:
Answers:

If I understand your question, here’s one way. Say you have:

a = [4.1, 6.21, 1.0]

so here’s some code…

def array_in_array(scalarlist):
    return [(x,) for x in scalarlist]

Which leads to:

In [72]: a = [4.1, 6.21, 1.0]

In [73]: a
Out[73]: [4.1, 6.21, 1.0]

In [74]: def array_in_array(scalarlist):
   ....:     return [(x,) for x in scalarlist]
   ....: 

In [75]: b = array_in_array(a)

In [76]: b
Out[76]: [(4.1,), (6.21,), (1.0,)]