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    <p>You can use <a href="http://www.numpy.org" rel="nofollow">Numpy</a> (I hope this is not fancy for you):</p> <pre><code>import numpy dataset2D = [ [6, 4], [0, 0, 0, 1], [1, 0, 2, 0], [2, 2, 0, 1], [1, 1, 1, 0], [0, 0, 1, 1], [1, 0, 2, 1] ] dataset2D_size = dataset2D[0] dataset2D = numpy.array(dataset2D) partition2D = [ ['A', '1', '2', '4'], ['B', '3', '5'], ['C', '6'] ] for partition in partition2D: label = partition[0] row_indices = [int(i) for i in partition[1:]] # Take the specified rows rows = dataset2D[row_indices] # Iterate the columns (this is the power of Python!) for column in zip(*rows): # Now, column will contain one column of data from specified row indices print column, # Apply your formula here print </code></pre> <p>or <strong>if you don't want to install Numpy</strong>, here is what you can do (this is what you want, actually):</p> <pre><code>dataset2D = [ [6, 4], [0, 0, 0, 1], [1, 0, 2, 0], [2, 2, 0, 1], [1, 1, 1, 0], [0, 0, 1, 1], [1, 0, 2, 1] ] partition2D = [ ['A', '1', '2', '4'], ['B', '3', '5'], ['C', '6'] ] dataset2D_size = dataset2D[0] for partition in partition2D: label = partition[0] row_indices = [int(i) for i in partition[1:]] rows = [dataset2D[row_idx] for row_idx in row_indices] for column in zip(*rows): print column, print </code></pre> <p>both will print:</p> <pre> (0, 1, 1) (0, 0, 1) (0, 2, 1) (1, 0, 0) (2, 0) (2, 0) (0, 1) (1, 1) (1,) (0,) (2,) (1,) </pre> <p><strong>Explanation of second code (without Numpy)</strong>:</p> <pre><code>[dataset2D[row_idx] for row_idx in row_indices] </code></pre> <p>This is basically you take each row (<code>dataset2D[row_idx]</code>) and collate them together as a list. So the result of this expression is a list of lists (which comes from the specified row indices)</p> <pre><code>for column in zip(*rows): </code></pre> <p>Then <code>zip(*rows)</code> will <strong>iterate column-wise</strong> (the one you want). This works by taking the first element of each row, then combine them together to form a <a href="http://docs.python.org/release/1.5.1p1/tut/tuples.html" rel="nofollow">tuple</a>. In each iteration, the result is stored in variable <code>column</code>.</p> <p>Then inside the <code>for column in zip(*rows):</code> you already have your intended column-wise iterated elements from specified rows!</p> <p>To apply your formula, just change the <code>print column,</code> into the stuff you wanna do. For example I modify the code to include row and column number:</p> <pre><code>print 'Processing partition %s' % label for (col_num, column) in enumerate(zip(*rows)): print 'Column number: %d' % col_num for (row_num, element) in enumerate(column): print '[%d,%d]: %d' % (row_indices[row_num], col_num, element) </code></pre> <p>which will result in:</p> <pre> Processing partition A Column number: 0 [1,0]: 0 [2,0]: 1 [4,0]: 1 Column number: 1 [1,1]: 0 [2,1]: 0 [4,1]: 1 Column number: 2 [1,2]: 0 [2,2]: 2 [4,2]: 1 Column number: 3 [1,3]: 1 [2,3]: 0 [4,3]: 0 Processing partition B Column number: 0 [3,0]: 2 [5,0]: 0 Column number: 1 [3,1]: 2 [5,1]: 0 Column number: 2 [3,2]: 0 [5,2]: 1 Column number: 3 [3,3]: 1 [5,3]: 1 Processing partition C Column number: 0 [6,0]: 1 Column number: 1 [6,1]: 0 Column number: 2 [6,3]: 2 Column number: 3 [6,3]: 1 </pre> <p>I hope this helps.</p>
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    1. POIterate over two nested 2D lists where list2 has list1's row numbers
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    1. POIterate over two nested 2D lists where list2 has list1's row numbers
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    1. COThis looks good. However dataset2d also has two numbers in the first row-> 6,4 where 6 is number of rows I need to consider, and 4 is number of columns.
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    2. COOh, so 6,4 is also part of the dataset2d? You can just take the second row onwards to a variable to get rid of the first row =)
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    3. COanswer edited =D
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