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<div><h1 id="ex:meansd">6.5 Foreach Datum Loops</h1>
<p>Foreach datum loops are similar to foreach loops in that they run a script block once for each item in a list. In this case, however, the list in question is the list of datapoints in a file. The syntax of the <tt class="tt">foreach datum</tt> command<a name="a0000000586" id="a0000000586"></a> is similar to that of the commands met in the previous chapter for acting upon datafiles: the standard modifiers <tt class="tt">every</tt>, <tt class="tt">index</tt>, <tt class="tt">select</tt> and <tt class="tt">using</tt> can be used to select which columns of the datafile, and which subset of the datapoints, should be used: </p><pre>
foreach datum i,j,name in "data.dat" using 1:2:"%s"%($3)
{
...
}
</pre><p>The <tt class="tt">foreach datum</tt> command<a name="a0000000587" id="a0000000587"></a> is followed by a comma-separated list of the variable(s) which are to be read from the datafile on each iteration of the loop. The <tt class="tt">using</tt> modifier specifies the columns or rows of data which are to be used to set the values of each variable. In this example, the third variable, <tt class="tt">name</tt>, is set using a quoted string, indicating that it will be set to equal whatever string of text is found in the third column of the datafile. </p><p> <span class="upshape"><span class="mdseries"><span class="rm">Calculating the Mean and Standard Deviation of Data.</span></span></span></p><div>
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<td style="border-top-style:solid; border-left:1px solid black; border-right:1px solid black; border-top-color:black; border-top-width:1px; text-align:left"><p> The following PyXPlot script calculates the mean and standard deviation of a set of datapoints using the <tt class="tt">foreach datum</tt> command<a name="a0000000588" id="a0000000588"></a>: </p></td>
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<td style="text-align:left; border-right:1px solid black; border-left:1px solid black"><p><tt class="tt">N_data = 0</tt><br /><tt class="tt">sum_x = 0</tt><br /><tt class="tt">sum_x2 = 0</tt><br /></p></td>
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<td style="text-align:left; border-right:1px solid black; border-left:1px solid black"><p><tt class="tt">foreach datum x in ’–’</tt><br /><tt class="tt">{</tt><br /><tt class="tt">N_data = N_data + 1</tt><br /><tt class="tt">sum_x = sum_x + x</tt><br /><tt class="tt">sum_x2 = sum_x2 + x**2</tt><br /><tt class="tt">}</tt><br /><tt class="tt">1.3</tt><br /><tt class="tt">1.2</tt><br /><tt class="tt">1.5</tt><br /><tt class="tt">1.1</tt><br /><tt class="tt">1.3</tt><br /><tt class="tt">END</tt><br /></p></td>
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<td style="text-align:left; border-right:1px solid black; border-left:1px solid black"><p><tt class="tt">mean = sum_x / N_data</tt><br /><tt class="tt">SD = sqrt(sum_x2 / N_data - mean**2)</tt><br /></p></td>
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<td style="text-align:left; border-right:1px solid black; border-left:1px solid black"><p><tt class="tt">print "Mean = %s"%(mean)</tt><br /><tt class="tt">print "SD = %s"%(SD)</tt> </p></td>
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<td style="border-bottom-style:solid; border-bottom-width:1px; border-left:1px solid black; border-right:1px solid black; text-align:left; border-bottom-color:black"><p>For the data supplied, a mean of <img src="images/img-0296.png" alt="$1.28$" style="vertical-align:0px;
width:31px;
height:12px" class="math gen" /> and a standard deviation of <img src="images/img-0297.png" alt="$0.133$" style="vertical-align:0px;
width:41px;
height:12px" class="math gen" /> are returned. </p></td>
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