[Numpy-discussion] array - dimension size of 1-D and 2-D examples

[Vinodhini Balusamy]

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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