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    <p>According to the first sentence in your question, you want to select values based on the values in another list or array.</p> <p>In numpy you can use indexing to get selected values from an array. I use <a href="http://docs.scipy.org/doc/numpy/reference/arrays.indexing.html#boolean" rel="nofollow">Boolean indexing</a> in the example. This avoids the need to append values to an existing array, but gives you a copy of the selected values as an array. You can combine multiple conditions using the <code>&amp;</code> or <code>|</code> operator, <a href="http://docs.scipy.org/doc/numpy/reference/routines.logic.html" rel="nofollow">logic functions</a> from numpy or your own functions. </p> <pre><code>In [1]: import numpy as np In [2]: size = int(1E7) In [3]: ar = np.arange(size) In [4]: ar2 = np.random.randint(100, size=size) In [5]: %timeit ar[(ar2 &gt; 50) &amp; (ar2 &lt; 70) | (ar2 == 42)] 10 loops, best of 3: 249 ms per loop </code></pre> <p>If you need every selection in a separate array based on different conditions (or ranges as given in the comment) you can do something like this:</p> <pre><code>conditions = [(10, 20), (20, 50)] # min, max as tuples in a list results = {} for condition in conditions: selection = ar[(ar2 &gt; condition[0]) &amp; (ar2 &lt; condition[1])] # do something with the selection ? results[condition] = selection print results </code></pre> <p>will give you something like that</p> <pre><code>{(20, 50): array([ 2, 6, 7, ..., 9999993, 9999997, 9999998]), (10, 20): array([ 1, 3, 66, ..., 9999961, 9999980, 9999999])} </code></pre> <p>You should avoid looping over a numpy array in general, but instead use vectorized functions to manipulate your arrays. </p>
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    1. COok, this sounds good. Suppose now I've a lot of selections. If the value pass `selection1`, put it in `ar1`, if pass `selection2` put in `ar2`, .... Selections are similar to `10 < x <= 20`, `20 < x <= 50`, ...
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    2. CO@wiso I adapted the example.
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    3. COthank you, but this is not what I've asked in my comment. As output I need different collections, one for `10<x<=20`, the second for `20<x<=50`, ...
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