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    <p>Sven's answer is the way to do it if you don't wish to further process matching values.<br> The following two examples return copies with only the matching values:</p> <pre><code>np.compress((25 &lt; a) &amp; (a &lt; 100), a).size </code></pre> <p>Or: </p> <pre><code>a[(25 &lt; a) &amp; (a &lt; 100)].size </code></pre> <p>Example interpreter session:</p> <pre><code>&gt;&gt;&gt; import numpy as np &gt;&gt;&gt; a = np.random.randint(200,size=100) &gt;&gt;&gt; a array([194, 131, 10, 100, 199, 123, 36, 14, 52, 195, 114, 181, 138, 144, 70, 185, 127, 52, 41, 126, 159, 39, 68, 118, 124, 119, 45, 161, 66, 29, 179, 194, 145, 163, 190, 150, 186, 25, 61, 187, 0, 69, 87, 20, 192, 18, 147, 53, 40, 113, 193, 178, 104, 170, 133, 69, 61, 48, 84, 121, 13, 49, 11, 29, 136, 141, 64, 22, 111, 162, 107, 33, 130, 11, 22, 167, 157, 99, 59, 12, 70, 154, 44, 45, 110, 180, 116, 56, 136, 54, 139, 26, 77, 128, 55, 143, 133, 137, 3, 83]) &gt;&gt;&gt; np.compress((25 &lt; a) &amp; (a &lt; 100),a).size 34 &gt;&gt;&gt; a[(25 &lt; a) &amp; (a &lt; 100)].size 34 </code></pre> <p>The above examples use a "bit-wise and" (&amp;) to do an element-wise computation along the two boolean arrays which you create for comparison purposes.<br> Another way to write Sven's excellent answer, for example, is: </p> <pre><code>np.bitwise_and(25 &lt; a, a &lt; 100).sum() </code></pre> <p>The boolean arrays contain <code>True</code> values when the condition matches, and <code>False</code> when it doesn't.<br> A bonus aspect of boolean values is that <code>True</code> is equivalent to 1 and <code>False</code> to 0. </p>
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    1. POHow to count values in a certain range in a Numpy array?
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    1. CO@Sevn and Adam, I am still pretty new to python ~6 months not very consistently though. Can you guys explain how and why your scripts work? Thank you
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    2. COOr point me towards where I can read up on it.
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    3. CO@Surfcast23: I added a bit of an explanation. Keep at it!
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