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POreplace blanks in numpy array
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copied!<p>The third column in my numpy array is Age. In this column about 75% of the entries are valid and 25% are blank. Column 2 is Gender and using some manipulation I have calculated the average age of the men in my dataset to be 30. The average age of women in my dataset is 28.</p> <p>I want to replace all blank Age values for men to be 30 and all blank age values for women to be 28.</p> <p>However I can't seem to do this. Anyone have a suggestion or know what I am doing wrong?</p> <p>Here is my code:</p> <pre><code># my entire data set is stored in a numpy array defined as x ismale = x[::,1]=='male' maleAgeBlank = x[ismale][::,2]=='' x[ismale][maleAgeBlank][::,2] = 30 </code></pre> <p>For whatever reason when I'm done with the above code, I type <code>x</code> to display the data set and the blanks still exist even though I set them to 30. Note that I cannot do <code>x[maleAgeBlank]</code> because that list will include some female data points since the female data points are not yet excluded.</p> <p>Is there any way to get what I want? For some reason, if I do <code>x[ismale][::,1] = 1</code> (setting the column with 'male' equal to 1), that works, but <code>x[ismale][maleAgeBlank][::,2] = 30</code> does not work.</p> <p>sample of array:</p> <pre><code>#output from typing x array([['3', '1', '22', ..., '0', '7.25', '2'], ['1', '0', '38', ..., '0', '71.2833', '0'], ['3', '0', '26', ..., '0', '7.925', '2'], ..., ['3', '0', '', ..., '2', '23.45', '2'], ['1', '1', '26', ..., '0', '30', '0'], ['3', '1', '32', ..., '0', '7.75', '1']], dtype='<U82') #output from typing x[0] array(['3', '1', '22', '1', '0', '7.25', '2'], dtype='<U82') </code></pre> <p>Note that I have changed column 2 to be 0 for female and 1 for male already in the above output</p>

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