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I am looking for coding examples to learn Numpy.

Usage would be dtype ='object'. To construnct array the code used would 

a= np.asarray(d, dtype ='object')

not np.asarray(d) or np.asarray(d, dtype='float32')

Is sorting any different than float32/64?

Coming from excel "cell" equations, wrapping my head around Row Column math.

Ex: 

A = array([['a',2,3,4],['b',5,6,2],['c',5,1,5]], dtype ='object')

[['a',2,3,4],
 ['b',5,6,2],
 ['c',5,1,5]])

Create new array with: How would I sort high to low by [3].

How calc for entire col. (1,1)- (1,0), Example without sorting A

 ['b',3],
 ['c',0]

How calc for enitre array (1,1) - (2,0) Example without sorting A

 ['b',2],
 ['c',-1]
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  • It is very difficult to ascertain what you are asking. Please consider editing your question to make it more readable. You notation is not clear. Commented Apr 12, 2011 at 19:54
  • Care to elaborate which tutorials you are following on. Please re-edit your question to focus on the most important issue you have doubts. Thanks Commented Apr 12, 2011 at 19:54
  • Why then I'm going through tutorials in your question? Thanks Commented Apr 12, 2011 at 19:59
  • Please elaborate more on what you mean by dtype ='object' and is sorting any different than float32/64. Your edit did not really make the question any more understandable. Still care to elaborate what you mean by without sorting? FWIW, in Numpy indices like [i, j] are interpreted to mean (i+ 1)th row and (j+ 1)th column. Thanks Commented Apr 12, 2011 at 20:34
  • @user428862: Nope. I still don't know what your indexing means, for example b 5 - a 2 = 3 doesn't make sense. Commented Apr 12, 2011 at 23:43

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Despite the fact that I still cannot understand exactly what you are asking, here is my best guess. Let's say you want to sort A by the values in 3rd column:

A = array([['a',2,3,4],['b',5,6,2],['c',5,1,5]], dtype ='object')

ii = np.argsort(A[:,2])
print A[ii,:]

Here the rows have been sorted according to the 3rd column, but each row is left unsorted.

Subtracting all of the columns is a problem due to the string objects, however if you exclude them, you can for example subtract the 3rd row from the 1st by:

A[0,1:] - A[2,1:]

If I didn't understand the basic point of your question, then please revise it. I highly recommend you take a look at the numpy tutorial and documentation if you have not done so already:

http://docs.scipy.org/doc/numpy/reference/

http://docs.scipy.org/doc/numpy/user/

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6 Comments

So, in order to math, I would first have to create a second array with only numbers, no strings. Then do math (substractions of perceeding rows or row and column, then combine back the two arrays.... Is this what you getting at?
@user428862 - I'm still confused as to what you're asking as well, but if you're just trying to do math on columns, then just do something like x[:,3] = x[:,2] - x[:,1] to assign the 4th column to the result of the third column minus the second column. As Josh suggested, it sounds like you might want to read the various tutorials and try to re-phrase your question. Also, object arrays are probably not what you really want, but that's a different story altogether...
@Joe, thanks. object array are what I'm using because of strings. I need the strings in arrays, What tutorials would cover the above math array stuff?
@user428862: As far as tutorials go, you should look at the links I provided.
@user428862: If you are only using the strings as labels, consider using numpy record arrays. See: docs.scipy.org/doc/numpy/reference/generated/… or docs.scipy.org/doc/numpy/user/basics.rec.html
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