average

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.average takes an optional weight parameter. If it is not supplied they are equivalent. Take a look at the source code: Mean , Average np.mean: try: mean = a.mean except AttributeError: return _wrapit(a, 'mean', axis, dtype, out) return mean(axis, dtype, out) np.average: ... if weights is None : avg = a.mean(axis) scl = avg.dtype.type(a.size/avg.size) else: #code

I have a model in which I use Django ORM to extract Avg of values from the table. I want to Round that Avg value, how do I do this? See below I am extracting Avg price from Prices model grouped by date in format YYYY-MM, I want to automatically extract the average values rounded to the closest number. rs = Prices.objects.all.extra(select={ 'for_date': 'CONCAT(CONCAT(extract( YEAR from for_date ), "-"), LPAD(extract(MONTH from for_date), 2, "00"))' }).values('for_date').annotate(price=Avg('price')).order_by('-for_date') Use Func() expressions . Here's an example using the Book model from Django

I have this dataframe "df1" as example which is actually part of a much larger one (15 years): X1 X2 3798 2009-12-29 0 3799 2009-12-30 0 3800 2009-12-31 0 3802 2010-01-02 0 3803 2010-01-03 2.1 3804 2010-01-04 0 3805 2010-01-05 0 3806 2010-01-06 0 3807 2010-01-07 0 3808 2010-01-08 0 3809 2010-01-09 0 3810 2010-01-10 6.8 3811 2010-01-12 0 3812 2010-01-13 0 3813 2010-01-14 17.7 3814 2010-01-16 0 3815 2010-01-17 0 3816 2010-01-18 1.5 3817 2010-01-19 0 3818 2010-01-20 0 3819 2010-01-21 0 3820 2010-01-22 0 3821 2010-01-23 0 3822 2010-01-24 0 3823 2010-01-25 0 3824 2010-01-26 0 3825 2010-01-27 4.5

I'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 <Integer> marks = new ArrayList(); Collections.addAll(marks, (Integer.parseInt(markInput.getText()))); private void analyzeButtonActionPerformed(java.awt.event.ActionEvent evt) { analyzeTextArea.setText("Class average:" + calculateAverage(marks)); } private int calculateAverage(List <Integer> marks) { int sum = 0; for (int i=0; i<

I would like to know if I can get the average of a sum in one single SQL SERVER request, Have tried to do it with the following request but it doesn't work: SELECT t.client, AVG(SUM(t.asset)) AS Expr1 FROM TABLE t GROUP BY t.client Lukasz Lysik I think your question needs a bit of explanation. If you want to take the sums grouped by t.client you can use: SELECT t.client, SUM(t.asset) FROM the-table t GROUP BY t.client Then, if you want to take the average of this sume, just make: SELECT AVG(asset_sums) FROM ( SELECT t.client, SUM(t.asset) AS asset_sums FROM the-table t GROUP BY t.client ) as

I have an hourly dataframe in the following format over several years: Date/Time Value 01.03.2010 00:00:00 60 01.03.2010 01:00:00 50 01.03.2010 02:00:00 52 01.03.2010 03:00:00 49 . . . 31.12.2013 23:00:00 77 I would like to average the data so I can get the average of hour 0, hour 1... hour 23 of each of the years. So the output should look somehow like this: Year Hour Avg 2010 00 63 2010 01 55 2010 02 50 . . . 2013 22 71 2013 23 80 Does anyone know how to obtain this in pandas? Note: Now that Series have the dt accessor it's less important that date is the index, though Date/Time still needs