mean

问题 I have 'mydata_hourly' with 3 station (actually more) and their hourly temperature values over one year. This gives me 8760 hourly measurements in one year. Now I want to have the same structure but with the (365) 24h-average means 'mydata_daily'. I have tried something with a for loop, this didn't work out. I have heard something about an aggregate function. I found something with a timestamp, what I don't have unfortunately. . my_data_hourly <- structure(c(8.29, 7.96, 8.14, 7.27, 7.37, 7.3,

问题 I'm loading in a csv file line by line because it has ~800 million lines in it and there are many of these files which I need to analyse so loading in parallel is paramount and loading line by line is also required so as to not blow up the memory. I have been given an answer to how to calculate the number of entries in which unique IDs are present throughout the dataset using collections.Counter() . (see Counting csv column occurrences on the fly in Python) But is there a way to calculate a

问题 Hi, I have some continuous x/y coordinates from a behavioural experiment, that I would like to average within groups using Pandas. I'm using a subset of the data here. data Out[11]: <class 'pandas.core.frame.DataFrame'> Int64Index: 2036 entries, 0 to 1623 Data columns (total 9 columns): id 2036 non-null values subject 2036 non-null values code 2036 non-null values acc 2036 non-null values nx 2036 non-null values ny 2036 non-null values rx 2036 non-null values ry 2036 non-null values reaction

问题 This question already has answers here : how to avoid the potential of an overflow when computing an average of times? (3 answers) Closed 6 months ago . I need to calculate the average of n numbers. N is unknown at compile time. Each of the numbers could be an int64_t type but I know that also average fits in int64_t type. Problem is that the sum of n numbers could be too large for int64_t. Any suggestions? 回答1: Average of two nos without overflow Average = (a / 2) + (b / 2) + (((a % 2) + (b

问题 I am trying to create a normalization value for a variable I am working with based on individual conference means and SDs. I found the conference means using the function: confavg=aggregate(base$AVG, by=list(base$confName), FUN=mean) And so after getting the means for the 31 conferences, I want to go back and for each individual player put these means in so I can easily calculate a normalization factor based on the conference mean. I have tried to create large ifelse or if statements where

问题 Consider the two vectors: v= [1 2 3 4 5 6 7] a=['a' 'b' 'c' 'a' 'a' 'a' 'd'] I want to find the mean of all entries in v whose corresponding entries in a is 'a'; i.e. test= mean(1,3,4,5) I have tried this for a start to catch the entries: for i=1:7 if abs(char(a(i))-char(c))==0; test(i)=v(i); end end test test = 1 0 0 4 5 6 PROBLEMS: It is assigning 0 for entries not found It is not considering last term 回答1: Try using the ismember function: >> help ismember ismember True for set member.

问题 I have a 16x10 panda dataframe with 1x35000 arrays (or NaN) in each cell. I want to take the element-wise mean over rows for each column. 1 2 3 ... 10 1 1x35000 1x35000 1x35000 1x35000 2 1x35000 NaN 1x35000 1x35000 3 1x35000 NaN 1x35000 NaN ... 16 1x35000 1x35000 NaN 1x35000 To avoid misunderstandings: take the first element of each array in the first column and take the mean. Then take the second element of each array in the first column and take the mean again. In the end I want to have a

问题 I am interested in calculating GPH anomalies in Matlab. I have a 3D matrix of lat, lon, and time. Where time is a daily GPH value for 32 years (1979-2010). The matrix is 95x38x11689. How do I compute a daily average across all years for each day of data, when the matrix is 3D? I am ultimately trying to compute the GPH anomaly from the difference of the daily value and the climatological mean of that given day. In other words, how do I compute the average of Jan. 1st dates for all years to

问题 I work with an image that I consider as a matrix. I want to turn a 800 x 800 matrix (A) into a 400 x 400 matrix (B) where the mean of 4 cells of the A matrix = 1 cell of the B matrix (I know this not a right code line) : B[1,1] =mean2(A[1,1 + 1,2 + 2,1 + 2,2]) and so on for the whole matrix ... B [1,2]=mean2(A[1,3 + 1,4 + 2,3 + 2,4 ]) I thought to : 1) Reshape the A matrix into a 2 x 320 000 matrix so I get the four cells I need to average next to each other and it is easier to deal with the

问题 In R, how can I generate N numbers that have a mean of X and a median of Y (at least close to). Or perhaps more generally, is there an algorithm for this? 回答1: There is an infinite number of solutions. Approximate algorithm: Generate n/2 numbers below the median Generate n/2 numbers above the median Add you desired median and check Add one number with enough weight to satisfy your mean -- which you can solve Example assuming you want a median of zero and a mean of twenty: R> set.seed(42) R>