aggregate

问题 Suppose I have view of data in bigquery Person | Amount | yearMonth --------------------------- AA | 100 | 201701 AA | 200 | 201702 AA | 300 | 201703 AA | 70 | 201704 AB | 10 | 201701 AB | 50 | 201702 AB | 60 | 201703 AB | 70 | 201704 AC | 70 | 201701 AC | 80 | 201702 AC | 30 | 201703 AC | 10 | 201704 Now, I need to get the average of this for the last 3 months for every person every month Expected Results: Person | Amount | yearMonth --------------------------- AA | 200 | 201703(avg of

问题 This question already has answers here : How to return array of string with mongodb aggregation (2 answers) Closed 2 years ago . As we know if we want to get an array of _id we can do: db.collections.distinct("_id"); My question is how can I get an array of _id if I need to do a complicate logic with aggregate. Ex: db.getCollection('users').aggregate({ $match : { is_register_completed : { $ne : true} } } //other operator like $lookup, $group , { $project : {_id:1} } ) I get { "_id" : "1", "

问题 Let's assume I have a raster representing land use classes in a certain resolution. I have to aggregate this raster with R to a coarser resolution and a modal value approach, in order to have the most dominating cell value in the coarser raster. This is easily achieved with m <- aggregate(r, fact = 3, fun = modal, na.rm = TRUE) However, I would like to weight the different land use classes – e.g. forest class (code 1) has a weight of 4 while water class (code 2) has a weight of 2 and street

问题 Considering the following Documents in "Words": [{ _id: 1, usages: 2, word: "Name" }, { _id: 2, usages: 1, word: "Street" }, { _id: 3, usages: 1, word: "House" }, { _id: 4, usages: 3, word: "Table" }, { _id: 5, usages: 3, word: "Bread" }, { _id: 6, usages: 4, word: "Door" }] How can i get all the records where the number of usages is the lowest or highest? Lowest should return id 2 and 3(and their word), highest should return id 6 with its word. I need to aggregate this data into a random

问题 Let's say that we have the following matrix: x<- as.data.frame(cbind(c("A","A","A","B","B","B","B","B","C","C","C","C","C","D","D","D","D","D"), c(1,2,3,1,2,3,4,5,1,2,3,4,5,1,2,3,4,5), c(14,28,42,14,46,64,71,85,14,28,51,84,66,22,38,32,40,42))) colnames(x)<- c("ID","Visit", "Age") The first column represents subject ID, the second a list of observations and the third the age at each of this consecutive observations. Which would be the easiest way of finding visits where the age is wrong

问题 Related to Dataframe aggregate method passing list problem and Pandas fails to aggregate with a list of aggregation functions Consider this dataframe import pandas as pd import numpy as np df = pd.DataFrame(index=range(10)) df['a'] = [ 3 * x for x in range(10) ] df['b'] = [ 1 -2 * x for x in range(10) ] According to the documentation for aggregate you should be able to specify which columns to aggregate using a dict like this: df.agg({'a' : 'mean'}) Which returns a 13.5 But if you try to

问题 EDIT: I'm told that making you guys read means I get less attention. My apologies. Here's a simpler version: Bill got $100 dollars worth of items from a store. He wants to return enough of the items to get exactly $30 dollars back. The store has a Point of Return system that will help him do this. Here is the data after he scans his items: item ¦ price ¦ socks 4.00 cheap tv 22.00 book on tape 9.00 book on paper 7.00 party hats 3.00 picture frame 10.00 hammer 5.00 juicer 16.00 mysql guide 24

问题 In C++11, are the aggregates allowed to be copied with curly-braces syntax? I have the following code: struct s { int x; }; template<class T> struct holder { template<class A> holder(A&& x) : t{x} {} T t; }; Each one of the statements below works. auto s1 = s{1}; auto s2(s1); auto s3{s1}; ///NOTE : this works! However, the second statement below raises the error cannot convert 's' to 'int' in initialization . holder<s> h{5}; holder<s> h1{s{5}}; I am using gcc 4.8.2. Why do I get this error?

问题 This question already has an answer here : Data.table meta-programming (1 answer) Closed 3 years ago . I would like to aggregate some columns by a list of columns in a data.table. However, I would like to refrain from using the column names outside the quotation marks (in the by = .(desiredColumn1, desiredColumn2) , that is). I am happy with using either the column names or the column indices. For example: library(data.table) x = as.data.table(iris) x[, sum(Sepal.Width), by = .(Sepal.Length,

问题 I would like to aggregate a table (tab) by two columns (sequence and program) to get the top row of samplesize (FUN=head). sq <- c(1,1,1,1,1,1) prog<- c('A','A','B','B','C','C') ss <- c(47,47,28,28,47,47) tab<- data.frame(sq,prog,ss) Aggregate is giving me an odd result in that if the sample size is the same for a DIFFERENT combination of sequence and program- it omits it. agg <- aggregate(cbind(sq,prog) ~ ss, data = tab, FUN=head,1,na.rm=TRUE) I'm confused why this is occurring and why it is