cumulative-sum

问题 I have a table with the following columns: reportDate DATETIME and losses CURRENCY and of course the ID column. How do I write a query that will return a table with a running total of the losses column? Each date will have multiple entries so i think they will need use Sum() for each date. I know this has to do with the DSum function but im still lost on this one. It should look something like Month Losses Cum ----- ------ ----- Jan $3,000 $3,000 Feb $2,000 $5,000 Mar $1,500 $6,500 Having a

问题 I'm trying to calculate a running count (i.e., cumulative sum) that is conditional on other variables and that can reset for particular values on another variable. I'm working in R and would prefer a dplyr -based solution, if possible. I'd like to create a variable for the running count, cumulative , based on the following algorithm: Calculate the running count ( cumulative ) within combinations of id and age Increment running count ( cumulative ) by 1 for every subsequent trial where

问题 I have a table containing donations, and I am now creating a page to view statistics. I would like to fetch monthly data from the database with gross and cumulative gross. mysql> describe donations; +------------------+------------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +------------------+------------------+------+-----+---------+----------------+ | id | int(10) unsigned | NO | PRI | NULL | auto_increment | | transaction_id | varchar(64

问题 I have a simple binary vector a which I try to translate into vector b using the R function cumsum . However, cumsum does not exactly return vector b . Here is an example: a <- c(1,0,0,0,1,1,1,1,0,0,1,0,0,0,1,1) b <- c(1,2,2,2,3,4,5,6,7,7,8,9,9,9,10,11) > cumsum(a) [1] 1 1 1 1 2 3 4 5 5 5 6 6 6 6 7 8 The problem is that whenever a 0 appears in vector a then the previous number should be increased by 1 but only for the first 0. The remaining ones are given the same value. Any advise would be

问题 I am struggling to plot the PDF and CDF graphs of where Sn=X1+X2+X3+....+Xn using central limit theorem where n = 1; 2; 3; 4; 5; 10; 20; 40 I am taking Xi to be a uniform continuous random variable for values between (0,3). Here is what i have done so far - close all %different sizes of input X %N=[1 5 10 50]; N = [1 2 3 4 5 10 20 40]; %interval (1,6) for random variables a=0; b=3; %to store sum of differnet sizes of input for i=1:length(N) %generates uniform random numbers in the interval X

问题 Suppose I have the following DataFrame: df = pd.DataFrame({'Event': ['A', 'B', 'A', 'A', 'B', 'C', 'B', 'B', 'A', 'C'], 'Date': ['2019-01-01', '2019-02-01', '2019-03-01', '2019-03-01', '2019-02-15', '2019-03-15', '2019-04-05', '2019-04-05', '2019-04-15', '2019-06-10'], 'Sale': [100, 200, 150, 200, 150, 100, 300, 250, 500, 400]}) df['Date'] = pd.to_datetime(df['Date']) df Event Date Sale A 2019-01-01 100 B 2019-02-01 200 A 2019-03-01 150 A 2019-03-01 200 B 2019-02-15 150 C 2019-03-15 100 B

问题 For example I have the bellow table (tb_transaction) id_trans date_trans production_plant dead_plant distribution_plant 25 2017-12-31 1000 100 200 26 2018-01-17 150 0 0 27 2018-02-07 0 50 100 28 2018-03-07 250 0 75 29 2018-05-10 500 50 0 Than I try to make a report table for this Year, like bellow table month EarlyStock production dead LivePlant Distri EndStock January 150 0 150 0 150 February 0 50 -50 100 -150 March 250 0 250 75 175 April 0 0 0 0 0 May 500 50 450 0 450 June 0 0 0 0 0 July 0

问题 I have a datframe with around 200 features and 3000 rows. These data samples are logged in different time, basically one per month, as shown in the below example in “col101”: 0 col1 (id) col2. col3 …. col100 col101 (date) … col2000 (target value) 1 001 653. 675 …. 343.3 01-02-2017. … 1 2 001 673. 432 …. 387.3 01-03-2017. … 0 3 001 679. 528 …. 401.2 01-04-2017. … 1 4 001 685 223 …. 503.4 01-05-2017. … 1 5 002 343 428 …. 432.5 01-02-2017. … 0 6 002 479. 421 …. 455.3 01-03-2017. … 0 7 … … … …. …

问题 I'm new to R and struggling with the following combination of cumulative multiplication with the addition of extra constants. I'm looking to achieve the following in a dataframe: Variable_X Variable_Y Variable_Z X1 Y1 Y1*X1 = Z1 X2 Y2 (Z1+Y2)*X2 = Z2 X3 Y3 (Z2+Y3)*X3 = Z3 X4 Y4 (Z3+Y4)*X4 = Z4 Any help would be greatly appreciated. 回答1: library(Rcpp) cppFunction("NumericVector foo_cpp (NumericVector x, NumericVector y) { int n = x.size(), i; NumericVector z(n); double tmp = 0.0; for (i = 0; i

问题 Consider the following matrix, where the first column is the index, the second - is values, the third - is the cumulative sum which resets once the index changes: 1 1 1 % 1 1 2 3 % 1+2 1 3 6 % 3+3 2 4 4 % 4 2 5 9 % 4+5 3 6 6 % 6 3 7 13 % 6+7 3 8 21 % 13+8 3 9 30 % 21+9 4 10 10 % 10 4 11 21 % 10+11 How can one get the third column avoiding loops? I try the following: A = [1 1;... % Input 1 2;... 1 3;... 2 4;... 2 5;... 3 6;... 3 7;... 3 8;... 3 9;... 4 10;... 4 11]; CS = cumsum(A(:,2)); %