[Chicago] Question about accessing dictionary's elements.

[Lewit, Douglas]

Hi William,

I'm doing a KNN program (K-Nearest-Neighbors).  I'm attaching what I've
done so far.  It's not complete!  But I've made good progress I think.
 (The program won't work unless you also download the .txt file that the
program uses to read in the data.)

For this problem the data has to get split into two sets: a training set
(kind of like a control group in an experiment) and the test set (the
experimental group or its equivalent).  I have to use the K smallest
normalized distances to make a guess about which class the records in the
Training Set belong to.  (There are six classes: {1, 2, 3, 5, 6, 7}.
There's no class #4.)

This problem has given me a massive headache, but I think I'm almost done
with it.  All that's left really is to use one of the algorithms to make a
decision about which class each Test record should be assigned to.

Thanks for the feedback!

Best,

Douglas.


On Sat, Sep 19, 2015 at 10:45 AM, William E. S. Clemens <
wesclemens at gmail.com> wrote:

> I would agree that Jimmy's solution is the correct one for doing this. But
> I would avoid setting up your data structure in this manner. A dict is a
> hash table and it is be extremely fast a looking up a value by key.
>
> You are building an array of the keys to linearly search. This operation
> is going to be slow and will not scale well. If you described what this
> data is and what your trying todo with it. I maybe able to suggest a better
> data structure for storing and accessing it.
>
>
>
>
> --
> William Clemens
> Phone: 847.485.9455
> E-mail: wesclemens at gmail.com
>
> On Sat, Sep 19, 2015 at 10:02 AM, Lewit, Douglas <d-lewit at neiu.edu> wrote:
>
>> I love it!  Thanks Jim.
>>
>> On Sat, Sep 19, 2015 at 8:09 AM, Jimmy Calahorrano via Chicago <
>> chicago at python.org> wrote:
>>
>>> is more elegant but not sure if is the best option:
>>>
>>>
>>> [A[key] for key in A.keys() if key[0] == 1]
>>>
>>>
>>>
>>> --------------------------------------------
>>> On Sat, 9/19/15, Lewit, Douglas <d-lewit at neiu.edu> wrote:
>>>
>>>  Subject: [Chicago] Question about accessing dictionary's elements.
>>>  To: "The Chicago Python Users Group" <chicago at python.org>
>>>  Date: Saturday, September 19, 2015, 7:43 AM
>>>
>>>  Hi
>>>  guys,
>>>  I have a problem and not
>>>  sure how to address it.  Let's say I have a simple
>>>  dictionary such as.
>>>  A = { (1, 2) : 10, (1, 3) :
>>>  15, (1, 4) : 50, (2, 0) : 2, (2, 5) : 8, (2, 12) : 19
>>>  }
>>>  I would like to access any
>>>  and all tuples whose first value is 1 or let's say 2.
>>>  How would I do that?
>>>  So what I'm trying to
>>>  go for is:
>>>  A[(1, placeholder for any
>>>  int value)] thus giving me all the values that correspond to
>>>  (1, #).  Not really sure how to go about this.  Unless....
>>>  I suppose I could do something like
>>>  this:
>>>  for key in
>>>  A:     if list(key)[0]
>>>  == 1:
>>>  print(A[key])  #### Or whatever I want to do with the
>>>  number.
>>>  Hmmm.... maybe that would
>>>  work, but is there a more "elegant" way to do
>>>  this?  Is there any "pattern matching" in Python
>>>  so that I could do this:
>>>  A[(1, #placeholder for any
>>>  int )]
>>>  Hey, thanks for your
>>>  help.
>>>  By the way, has anyone seen
>>>  the book LEARNING PYTHON by Mark Lutz?  Wow!  Full of
>>>  great information, but the book is HUGE!!!  I'll have
>>>  serious back problems if I carry that thing around in my
>>>  backpack!  There's something about small, lightweight
>>>  books that I really prefer.  (And then there's eBooks,
>>>  but that's a horse of a different color in my
>>>  opinion.)
>>>  Have a great weekend and
>>>  I'm looking forward to some ideas on the above
>>>  problem.  Thanks in advance.
>>>  Best,
>>>  Douglas
>>>  L.
>>>
>>>  -----Inline Attachment Follows-----
>>>
>>>  _______________________________________________
>>>  Chicago mailing list
>>>  Chicago at python.org
>>>  https://mail.python.org/mailman/listinfo/chicago
>>>
>>> _______________________________________________
>>> Chicago mailing list
>>> Chicago at python.org
>>> https://mail.python.org/mailman/listinfo/chicago
>>>
>>
>>
>> _______________________________________________
>> Chicago mailing list
>> Chicago at python.org
>> https://mail.python.org/mailman/listinfo/chicago
>>
>>
>
> _______________________________________________
> Chicago mailing list
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>
>
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159,1.51776,13.53,3.41,1.52,72.04,0.58,8.79,0.00,0.00,3
160,1.51796,13.50,3.36,1.63,71.94,0.57,8.81,0.00,0.09,3
161,1.51832,13.33,3.34,1.54,72.14,0.56,8.99,0.00,0.00,3
162,1.51934,13.64,3.54,0.75,72.65,0.16,8.89,0.15,0.24,3
163,1.52211,14.19,3.78,0.91,71.36,0.23,9.14,0.00,0.37,3
164,1.51514,14.01,2.68,3.50,69.89,1.68,5.87,2.20,0.00,5
165,1.51915,12.73,1.85,1.86,72.69,0.60,10.09,0.00,0.00,5
166,1.52171,11.56,1.88,1.56,72.86,0.47,11.41,0.00,0.00,5
167,1.52151,11.03,1.71,1.56,73.44,0.58,11.62,0.00,0.00,5
168,1.51969,12.64,0.00,1.65,73.75,0.38,11.53,0.00,0.00,5
169,1.51666,12.86,0.00,1.83,73.88,0.97,10.17,0.00,0.00,5
170,1.51994,13.27,0.00,1.76,73.03,0.47,11.32,0.00,0.00,5
171,1.52369,13.44,0.00,1.58,72.22,0.32,12.24,0.00,0.00,5
172,1.51316,13.02,0.00,3.04,70.48,6.21,6.96,0.00,0.00,5
173,1.51321,13.00,0.00,3.02,70.70,6.21,6.93,0.00,0.00,5
174,1.52043,13.38,0.00,1.40,72.25,0.33,12.50,0.00,0.00,5
175,1.52058,12.85,1.61,2.17,72.18,0.76,9.70,0.24,0.51,5
176,1.52119,12.97,0.33,1.51,73.39,0.13,11.27,0.00,0.28,5
177,1.51905,14.00,2.39,1.56,72.37,0.00,9.57,0.00,0.00,6
178,1.51937,13.79,2.41,1.19,72.76,0.00,9.77,0.00,0.00,6
179,1.51829,14.46,2.24,1.62,72.38,0.00,9.26,0.00,0.00,6
180,1.51852,14.09,2.19,1.66,72.67,0.00,9.32,0.00,0.00,6
181,1.51299,14.40,1.74,1.54,74.55,0.00,7.59,0.00,0.00,6
182,1.51888,14.99,0.78,1.74,72.50,0.00,9.95,0.00,0.00,6
183,1.51916,14.15,0.00,2.09,72.74,0.00,10.88,0.00,0.00,6
184,1.51969,14.56,0.00,0.56,73.48,0.00,11.22,0.00,0.00,6
185,1.51115,17.38,0.00,0.34,75.41,0.00,6.65,0.00,0.00,6
186,1.51131,13.69,3.20,1.81,72.81,1.76,5.43,1.19,0.00,7
187,1.51838,14.32,3.26,2.22,71.25,1.46,5.79,1.63,0.00,7
188,1.52315,13.44,3.34,1.23,72.38,0.60,8.83,0.00,0.00,7
189,1.52247,14.86,2.20,2.06,70.26,0.76,9.76,0.00,0.00,7
190,1.52365,15.79,1.83,1.31,70.43,0.31,8.61,1.68,0.00,7
191,1.51613,13.88,1.78,1.79,73.10,0.00,8.67,0.76,0.00,7
192,1.51602,14.85,0.00,2.38,73.28,0.00,8.76,0.64,0.09,7
193,1.51623,14.20,0.00,2.79,73.46,0.04,9.04,0.40,0.09,7
194,1.51719,14.75,0.00,2.00,73.02,0.00,8.53,1.59,0.08,7
195,1.51683,14.56,0.00,1.98,73.29,0.00,8.52,1.57,0.07,7
196,1.51545,14.14,0.00,2.68,73.39,0.08,9.07,0.61,0.05,7
197,1.51556,13.87,0.00,2.54,73.23,0.14,9.41,0.81,0.01,7
198,1.51727,14.70,0.00,2.34,73.28,0.00,8.95,0.66,0.00,7
199,1.51531,14.38,0.00,2.66,73.10,0.04,9.08,0.64,0.00,7
200,1.51609,15.01,0.00,2.51,73.05,0.05,8.83,0.53,0.00,7
201,1.51508,15.15,0.00,2.25,73.50,0.00,8.34,0.63,0.00,7
202,1.51653,11.95,0.00,1.19,75.18,2.70,8.93,0.00,0.00,7
203,1.51514,14.85,0.00,2.42,73.72,0.00,8.39,0.56,0.00,7
204,1.51658,14.80,0.00,1.99,73.11,0.00,8.28,1.71,0.00,7
205,1.51617,14.95,0.00,2.27,73.30,0.00,8.71,0.67,0.00,7
206,1.51732,14.95,0.00,1.80,72.99,0.00,8.61,1.55,0.00,7
207,1.51645,14.94,0.00,1.87,73.11,0.00,8.67,1.38,0.00,7
208,1.51831,14.39,0.00,1.82,72.86,1.41,6.47,2.88,0.00,7
209,1.51640,14.37,0.00,2.74,72.85,0.00,9.45,0.54,0.00,7
210,1.51623,14.14,0.00,2.88,72.61,0.08,9.18,1.06,0.00,7
211,1.51685,14.92,0.00,1.99,73.06,0.00,8.40,1.59,0.00,7
212,1.52065,14.36,0.00,2.02,73.42,0.00,8.44,1.64,0.00,7
213,1.51651,14.38,0.00,1.94,73.61,0.00,8.48,1.57,0.00,7
214,1.51711,14.23,0.00,2.08,73.36,0.00,8.62,1.67,0.00,7
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