average

问题 I have values in an Excel file like this: QR | QR AVG | val1 | q1 5 q1 3 q1 4 q2 7 q2 9 q3 10 q3 11 q3 12 q3 11 q4 5 q5 5 q5 7 And I would like the QR AVG field to represent the average value partitioned by different QR values. In other words, I'd like to have the following values after my calculation: QR | QR AVG | val1 | q1 4 5 q1 4 3 q1 4 4 q2 8 7 q2 8 9 q3 11 10 q3 11 11 q3 11 12 q3 11 11 q4 5 5 q5 6 5 q5 6 7 Where I don't know the exact number of rows that I will have, and I will be

问题 I am working on numpy and I have a number of arrays with the same size and shape like: a= [153 186 0 258] b=[156 136 156 0] c=[193 150 950 757] I want to have average of the arrays, but I want the program to ignore the zero values in the computation. So, the resulting array for this example will be: d=[167.333 157.333 553 507.5] this is the result of this computation: d=[(153+156+193)/3 (186+136+150)/3 (156+950)/2 (258+757)/2] . Is it possible to do that? 回答1: >>> import numpy as np >>> a =

问题 I have a data.frame from this code: my_df = data.frame("read_time" = c("2010-02-15", "2010-02-15", "2010-02-16", "2010-02-16", "2010-02-16", "2010-02-17"), "OD" = c(0.1, 0.2, 0.1, 0.2, 0.4, 0.5) ) which produces this: > my_df read_time OD 1 2010-02-15 0.1 2 2010-02-15 0.2 3 2010-02-16 0.1 4 2010-02-16 0.2 5 2010-02-16 0.4 6 2010-02-17 0.5 I want to average the OD column over each distinct read_time (notice some are replicated others are not) and I also would like to calculate the standard

问题 My question is about how to write an SQL query to calculate the average time between successive events. I have a small table: event Name | Time stage 1 | 10:01 stage 2 | 10:03 stage 3 | 10:06 stage 1 | 10:10 stage 2 | 10:15 stage 3 | 10:21 stage 1 | 10:22 stage 2 | 10:23 stage 3 | 10:29 I want to build a query that get as an answer the average of the times between stage(i) and stage(i+1). For example, the average time between stage 2 and stage 3 is 5: (3+6+6)/3 = 5 回答1: Aaaaand with a

问题 What's the most efficient way to create a moving average or rolling sum in R? How do you do the rolling function along with a "group by"? 回答1: While zoo is great, sometimes there are simpler ways. If you data behaves nicely, and is evenly spaced, the embed() function effectively lets you create multiple lagged version of a time series. If you look inside the VARS package for vector auto-regression, you will see that the package author chooses this route. For example, to calculate the 3 period

问题 I have measured a handful of variables in 30 minute intervals. Time stamps are available in datevec or datenum format. I want to calculate ... a) ... daily averages and b) ... average values at time x , e.g. temperature at 11:30, temperature at 12:00, etc. averaged over my whole dataset. While this is, more or less, easily done with loops, I wonder if there is an easier / more convenient way to work with time-series, since this is a quite basic task after all? /edit 1: As per request: click

问题 I want to find the avg of the total of two columns. I want to count the total of col1 and the total of col2 then find the average(how many different rows they are in). I have managed to come up with a solution in the this sqlfiddle (also see below) is this the best way? I initially thought I would need to use the avg function but couldn't work it out using this. CREATE TABLE test ( id INT NOT NULL AUTO_INCREMENT PRIMARY KEY, uid INT, col1 INT, col2 INT ) DEFAULT CHARACTER SET utf8 ENGINE

问题 I'm having trouble when trying to calculate the average temperature by hour. I have a data frame with date , time (hh:mm:ss p.m./a.m.)and temperature . What I need is to extract the mean temperature by hour in order to plot daily variation of temperature. I'm new to R, but did a try with what I know: I first tried by transforming hours into numbers, then extracting the first two characters, and then to calculate the mean but it didn't work very well. Moreover I have so many files to analize

问题 I'm spreadsheeting my favorite albums and I'd like the good tracks on the album to count more for its average than the bad songs. I thought about geometric means, but those do the opposite of what I want. I found the p-mean, which approaches the maximum of the dataset as p goes to infinity: Is there any way to implement this formula in only one cell? If p=2, I can use sqrt(sumsq()) but I'm not sure how to implement it if p > 2. It's impractical for me to add adjacent cells in each column. 回答1

问题 Hye guys, I included a screenshot to help clarify my problem: http://i40.tinypic.com/mcrnmv.jpg. I'm trying to calculate some kind of moving average and moving standard deviation. The thing is I want to calculate the coefficients of variation (stdev/avg) for the actual value. Normally this is done by calculating the stdev and avg for the past 5 years. However sometimes there will be observations in my database for which I do not have the information of the past 5 years (maybe only 3, 2 etc).