I have to find the average of a list in Python. This is my code so far

    from functools import reduce

    l = [15, 18, 2, 36, 12, 78, 5, 6, 9]
    print(reduce(lambda x, y: x + y, l))

I&#39;ve got it so it adds together the values in the list, but I don&#39;t know how to make it divide into them?

Finding the average of a list

I am having problems adding all the elements of an array as well as averaging them out. How would I do this and implement it with the code I currently have? The elements are supposed to be defined as I have it below.

    &lt;script type=&quot;text/javascript&quot;&gt;
    //&lt;![CDATA[
    
    var i;
    var elmt = new Array();
    
    elmt[0] = &quot;0&quot;;
    elmt[1] = &quot;1&quot;;
    elmt[2] = &quot;2&quot;;
    elmt[3] = &quot;3&quot;;
    elmt[4] = &quot;4&quot;;
    elmt[5] = &quot;7&quot;;
    elmt[6] = &quot;8&quot;;
    elmt[7] = &quot;9&quot;;
    elmt[8] = &quot;10&quot;;
    elmt[9] = &quot;11&quot;;
    
    // Problem here
    for (i = 9; i &lt; 10; i++){
      document.write(&quot;The sum of all the elements is: &quot; + /* Problem here */ + &quot; The average of all the elements is: &quot; + /* Problem here */ + &quot;&lt;br/&gt;&quot;);
    }   
    
    //]]&gt;
    &lt;/script&gt;

How to compute the sum and average of elements in an array?

I notice that 

    In [30]: np.mean([1, 2, 3])
    Out[30]: 2.0
    
    In [31]: np.average([1, 2, 3])
    Out[31]: 2.0

However, there should be some differences, since after all they are two different functions.

**What are the differences between them?**


np.mean() vs np.average() in Python NumPy?

I have a numpy array. I want to create a new array which is the average over every consecutive triplet of elements. So the new array will be a third of the size as the original.  

As an example:


     np.array([1,2,3,1,2,3,1,2,3])

should return the array:

     np.array([2,2,2])

Can anyone suggest an efficient way of doing this? I&#39;m drawing blanks.

Averaging over every n elements of a numpy array

Example:

    $a[] = &#39;56&#39;;
    $a[] = &#39;66&#39;;
    $a[] = &#39;&#39;;
    $a[] = &#39;58&#39;;
    $a[] = &#39;85&#39;;
    $a[] = &#39;&#39;;
    $a[] = &#39;&#39;;
    $a[] = &#39;76&#39;;
    $a[] = &#39;&#39;;
    $a[] = &#39;57&#39;;

Actually how to find average value from this array excluding empty. please help to resolve this problem.

How to find average from array in php?

I&#39;m trying to use the below code to calculate the average of a set of values that a user enters and display it in a `jTextArea` but it does not work properly. Say, a user enters 7, 4, and 5, the program displays 1 as the average when it should display 5.3  

      ArrayList &lt;Integer&gt; marks = new ArrayList();
      Collections.addAll(marks, (Integer.parseInt(markInput.getText())));
    
      private void analyzeButtonActionPerformed(java.awt.event.ActionEvent evt) {
  		  analyzeTextArea.setText(&quot;Class average:&quot; + calculateAverage(marks));
      }
  
      private int calculateAverage(List &lt;Integer&gt; marks) {
    	  int sum = 0;
    	  for (int i=0; i&lt; marks.size(); i++) {
     		  	sum += i;
     	  }
     	  return sum / marks.size();
      }


What is wrong with the code?

Calculating average of an array list?

I have collection of TimeSpans, they represent time spent doing a task. Now I would like to find the average time spent on that task. It should be easy but for some reason I&#39;m not getting the correct average.

Here&#39;s my code:

    private TimeSpan? GetTimeSpanAverage(List&lt;TimeSpan&gt; sourceList)
    {
        TimeSpan total = default(TimeSpan);

        var sortedDates = sourceList.OrderBy(x =&gt; x);

        foreach (var dateTime in sortedDates)
        {
            total += dateTime;
        }
        return TimeSpan.FromMilliseconds(total.TotalMilliseconds/sortedDates.Count());
    }

Find average of collection of TimeSpans

I am playing in Python a bit again, and I found a neat book with examples. One of the examples is to plot some data. I have a .txt file with two columns and I have the data. I plotted the data just fine, but in the exercise it says: Modify your program further to calculate and plot the running average of the data, defined by:

    $Y_k=\frac{1}{2r}\sum_{m=-r}^r y_{k+m}$

where `r=5` in this case (and the `y_k` is the second column in the data file). Have the program plot both the original data and the running average on the same graph.

So far I have this:

    from pylab import plot, ylim, xlim, show, xlabel, ylabel
    from numpy import linspace, loadtxt
    
    data = loadtxt(&quot;sunspots.txt&quot;, float)
    r=5.0
    
    x = data[:,0]
    y = data[:,1]
    
    plot(x,y)
    xlim(0,1000)
    xlabel(&quot;Months since Jan 1749.&quot;)
    ylabel(&quot;No. of Sun spots&quot;)
    show()

So how do I calculate the sum? In Mathematica it&#39;s simple since it&#39;s symbolic manipulation (Sum[i, {i,0,10}] for example), but how to calculate sum in python which takes every ten points in the data and averages it, and does so until the end of points?

I looked at the book, but found nothing that would explain this :\

-----------------------------

heltonbiker&#39;s code did the trick ^^ :D


    from __future__ import division
    from pylab import plot, ylim, xlim, show, xlabel, ylabel, grid
    from numpy import linspace, loadtxt, ones, convolve
    import numpy as numpy
    
    data = loadtxt(&quot;sunspots.txt&quot;, float)
    
    def movingaverage(interval, window_size):
        window= numpy.ones(int(window_size))/float(window_size)
        return numpy.convolve(interval, window, &#39;same&#39;)
    
    x = data[:,0]
    y = data[:,1]
    
    
    plot(x,y,&quot;k.&quot;)
    y_av = movingaverage(y, 10)
    plot(x, y_av,&quot;r&quot;)
    xlim(0,1000)
    xlabel(&quot;Months since Jan 1749.&quot;)
    ylabel(&quot;No. of Sun spots&quot;)
    grid(True)
    show()

And I got this: 

![image][1]

Thank you very much ^^ :)


  [1]: http://i.stack.imgur.com/4TyaF.png

Finding moving average from data points in Python

I come up with this

    n=1;
    curAvg = 0;
    loop{
      curAvg = curAvg + (newNum - curAvg)/n;
      n++;
    }
I think highlights of this way are:&lt;br&gt;
- It avoids big numbers (and possible overflow if you would sum and then divide)&lt;br&gt;
- you save one register (not need to store sum)

The trouble might be with summing error - but I assume that generally there shall be balanced numbers of round up and round down so the error shall not sum up dramatically.

Do you see any pitfalls in this solution?
Have you any better proposal?

How to efficiently compute average on the fly (moving average)?

I have a continuous value for which I&#39;d like to calculate an [exponential moving average](http://en.wikipedia.org/wiki/Exponential_moving_average#Exponential_moving_average). Normally I&#39;d just use the standard formula for this:

* S&lt;sub&gt;n&lt;/sub&gt; = &amp;alpha;Y + (1-&amp;alpha;)S&lt;sub&gt;n-1&lt;/sub&gt;

where S&lt;sub&gt;n&lt;/sub&gt; is the new average, &amp;alpha; is the alpha, Y is the sample, and S&lt;sub&gt;n-1&lt;/sub&gt; is the previous average.

Unfortunately, due to various issues I don&#39;t have a consistent sample time. I may know I can sample at the most, say, once per millisecond, but due to factors out of my control, I may not be able to take a sample for several milliseconds at a time. A likely more common case, however, is that I simple sample a bit early or late: instead of sampling at 0, 1 and 2 ms. I sample at 0, 0.9 and 2.1 ms. I do anticipate that, regardless of delays, my sampling frequency will be far, far above the Nyquist limit, and thus I need not worry about aliasing.

I reckon that I can deal with this in a more-or-less reasonable way by varying the alpha appropriately, based on the length of time since the last sample.

Part of my reasoning that this will work is that the EMA &quot;interpolates linearly&quot; between the previous data point and the current one. If we consider calculating an EMA of the following list of samples at intervals t: [0,1,2,3,4]. We should get the same result if we use interval 2t, where the inputs become [0,2,4], right? If the EMA had assumed that, at t&lt;sub&gt;2&lt;/sub&gt; the value had been 2 since t&lt;sub&gt;0&lt;/sub&gt;, that would be the same as the interval t calculation calculating on [0,2,2,4,4], which it&#39;s not doing. Or does that make sense at all?

Can someone tell me how to vary the alpha appropriately? &quot;Please show your work.&quot; I.e., show me the math that proves that your method really is doing the right thing.

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