[Numpy-discussion] array - dimension size of 1-D and 2-D examples
Vinodhini Balusamy
me.vinob at gmail.com
Sat Dec 30 11:38:05 EST 2017
Thanks Derek for quick clarification.
Just one more question from the details you have provided which from my understanding strongly seems to be Design
[DEREK] You cannot create a regular 2-dimensional integer array from one row of length 3
>
> and a second one of length 0. Thus np.array chooses the next most basic type of
> array it can fit your input data in
Which is the case, only if an second one of length 0 is given.
What about the case 1 :
>>> x12 = np.array([[1,2,3]])
>>> x12
array([[1, 2, 3]])
>>> print(x12)
[[1 2 3]]
>>> x12.ndim
2
>>>
>>>
This seems to take 2 dimension.
I presumed the above case and the case where length 0 is provided to be treated same(I mean same behaviour).
Correct me if I am wrong.
Also, could u please point out any documentation to understand the logic behind creating elements of type list in case 2(with second grid of length 0) ? If possible. I am curious to understand.
Kind Rgds,
Vinodhini B
> On 30 Dec 2017, at 11:36 PM, Derek Homeier <derek at astro.physik.uni-goettingen.de> wrote:
>
> On 30 Dec 2017, at 11:37 am, Vinodhini Balusamy <me.vinob at gmail.com> wrote:
>>
>> Case 2:
>>>>>
>>>>> x12 = np.array([[1,2,3],[]])
>>>>> x12.ndim
>> 1
>>>>> print(x12)
>> [list([1, 2, 3]) list([])]
>>>>>
>> In case 2, I am trying to understand why it becomes 1 dimentional ?!?!
>>
>>
>> Case 3:
>>>>>
>>>>> x12 = np.array([1,2,3])
>>>>> x12.ndim
>> 1
>>>>> print(x12)
>> [1 2 3]
>>>>>
>> This seems reasonable to me to be considered as 1 dimensional.
>>
>> Would like to understand case 2 a bit more to get to know if i am missing something.
>> Will be much appreciated if someone to explain me a bit.
>>
> Welcome to the crowd!
> You cannot create a regular 2-dimensional integer array from one row of length 3
> and a second one of length 0. Thus np.array chooses the next most basic type of
> array it can fit your input data in - you will notice in case 2 the array actually has two
> elements of type ‘list’, and you can verify that
>
> In [1]: x12 = np.array([[1,2,3],[]])
> In [2]: x12.dtype
> Out[2]: dtype('O')
> In [3]: x12.shape
> Out[3]: (2,)
>
> i.e. it has created an array of dtype ‘object’, which is probably not what you expected
> (and nothing you could perform standard arithmetic operations on:
>
> In [4]: x12+1
> TypeError: can only concatenate list (not "int") to list
>
> HTH
> Derek
>
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