average

问题 I am trying to calculate the average scroll depth of a page on a website. In Google Analytics, I have events that fire at milestones of 10% increments—so when a user reaches 10% down the page, 20%, 30%, and so on. I have have a custom metrics for each milestone (so I can track via the metrics or via the events). My question is: with this information, how to I calculate the average scroll depth of the page ? Or in other words, how do I find the average distance a user will scroll down the page

问题 I have list of A, and I want to count average on it's field a. What's the best way to do it? class A { int a; int b; } void f() { var L = new List<A>(); for (int i=0; i<3; i++) { L.Add(new A(){a = i}); } } 回答1: Enumerable.Average has an overload that takes a Func<T, int> as an argument. using System.Linq; list.Average(item => item.a); 回答2: You could try this one: var average = ListOfA.Select(x=>x.a).Average(); where ListOfA is a List of objects of type A . 回答3: You can use Enumerable.Average

问题 [Current] I am importing a text file in which the first column has simulation time (0~150) the second column has the delay (0.01~0.02). 1.000000 0.010007 1.000000 0.010010 2.000000 0.010013 2.000000 0.010016 . . . 149.000000 0.010045 149.000000 0.010048 150.000000 0.010052 150.000000 0.010055 which gives me the plot: [Desired] I need to plot an average line on it like shown in the following image with red line: 回答1: Here is a gnuplot only solution with sample data: set table "test.data" set

问题 DataFrame where Date is datetime: Column | Date :-----------|----------------------: A | 2018-08-05 17:06:01 A | 2018-08-05 17:06:02 A | 2018-08-05 17:06:03 B | 2018-08-05 17:06:07 B | 2018-08-05 17:06:09 B | 2018-08-05 17:06:11 Return Table is; Column | Date :-----------|----------------------: A | 2018-08-05 17:06:02 B | 2018-08-05 17:06:09 回答1: For your example. Your data: df = pd.DataFrame(data=[['A', '2018-08-05 17:06:01'], ['A', '2018-08-05 17:06:02'], ['A', '2018-08-05 17:06:03'], ['B'

问题 I'm trying to obtain an average value for scores arrays and leave other values from the first object. I can't manage how to loop through the objects to achieve expected output. const bigArr = [ { bigDummyData: "string0", examples: [ { smallDD: "string00", scores: [1, 1, 5] }, { smallDD: "string01", scores: [2, 2, 4] }, { smallDD: "string02", scores: [2, 2, 6] }, ], }, { bigDummyData: "string1", examples: [ { smallDD: "string10", scores: [3, 3, 3] }, { smallDD: "string11", scores: [2, 2, 2] },

问题 Anyone know how I can set a default value for an average? I have a line like this... dbPlugins = (from p in dbPlugins select new { Plugin = p, AvgScore = p.DbVersions.Average(x => x.DbRatings.Average(y => y.Score)) }) .OrderByDescending(x => x.AvgScore) .Select(x => x.Plugin).ToList(); which throws an error becase I have no ratings yet. If I have none I want the average to default to 0. I was thinking this should be an extension method where I could specify what the default value should be.

问题 I have a Pandas dataframe with two columns which are speed and time . speed date 54.72 1:33:56 49.37 1:33:59 37.03 1:34:03 24.02 7:39:58 28.02 7:40:01 24.04 7:40:04 24.02 7:40:07 25.35 7:40:10 26.69 7:40:13 32.04 7:40:16 28.02 11:05:43 30.71 11:05:46 29.36 11:05:49 18.68 11:05:52 54.72 11:05:55 34.69 10:31:34 25.03 10:31:38 56.04 10:31:40 44.03 10:31:43 I want to calculate the average of speeds per bins of 30 minutes. For example, the average speed during the 4th bin (1:31 - 2:00) is (54.72 +

问题 I have made a subset from the dataframe 'Indometh' called 'indo': indo Subject time conc 1 1 0.25 1.50 13 2 0.50 1.63 24 3 0.50 1.49 25 3 0.75 1.16 34 4 0.25 1.85 35 4 0.50 1.39 36 4 0.75 1.02 46 5 0.50 1.04 57 6 0.50 1.44 58 6 0.75 1.03 I want to find what the average concentration for the subset is. I have used code but to no avail: mean(subset(indo, conc >1 & conc <2)) I know summary(indo) will show the mean of the concentration but wanted to know if there was another way I could do this

问题 searched for it but found no solution - if there is already one sry for asking but i would be thankful for a link I have a dataframe (df) like this: timestamp value 2016-03-11 07:37:40 24.6018 2016-03-11 07:37:45 24.6075 2016-03-11 07:37:50 24.599 2016-03-11 07:37:55 24.6047 2016-03-11 07:38:00 24.5905 2016-03-11 07:38:05 24.551 ... important start not at a even minute like 07:40:00 but 07:37:40 (could be any time) and i want to resample it - calculate mean values over e.g. 5 minutes labeled

问题 searched for it but found no solution - if there is already one sry for asking but i would be thankful for a link I have a dataframe (df) like this: timestamp value 2016-03-11 07:37:40 24.6018 2016-03-11 07:37:45 24.6075 2016-03-11 07:37:50 24.599 2016-03-11 07:37:55 24.6047 2016-03-11 07:38:00 24.5905 2016-03-11 07:38:05 24.551 ... important start not at a even minute like 07:40:00 but 07:37:40 (could be any time) and i want to resample it - calculate mean values over e.g. 5 minutes labeled