Question

我的数据结构如下：

Athletes = c("Gus", "Hudson", "Bobby", "Tom")
set.seed(400)
RawData <- data.frame(Name = rep((Athletes), each = 400),
                                Quarter = as.numeric(rep(1:4, each = 100)),
                                Sample = as.numeric(rep(1:100, each = 1)),
                                X = runif(400, 26, 30), 
                                Y = runif(400, 12, 16))

我希望计算每Athlete个Sample每个Quarter的每个X和Y对的位移。DistanceOutput <- RawData %>% arrange(Name, Sample, Quarter) %>% group_by(Name, Quarter) %>% mutate( lagX = lag(X, order_by=Sample), lagY = lag(Y, order_by=Sample)) %>% rowwise() %>% mutate(Distance = dist( matrix( c(X,Y,lagX,lagY),nrow=2,byrow=TRUE) )) %>% select(-lagX, -lagY)每data.frame。为此，我设置了以下代码：

> head(DistanceOutput, n=10)
Source: local data frame [10 x 6]

     Name Quarter Sample        X        Y Distance
   (fctr)   (dbl)  (dbl)    (dbl)    (dbl)    (dbl)
1   Bobby       1      1 27.82656 13.85830       NA
2   Bobby       2      1 27.37298 15.67940       NA
3   Bobby       3      1 28.74274 12.25703       NA
4   Bobby       4      1 26.63564 13.07924       NA
5   Bobby       1      2 26.32446 12.64722 1.929508
6   Bobby       2      2 26.88957 14.52096       NA
7   Bobby       3      2 27.53932 15.57959 3.533781
8   Bobby       4      2 28.03031 12.70763 1.443328
9   Bobby       1      3 29.68239 13.82739 3.559287
10  Bobby       2      3 29.43869 12.60890 3.186531

但是，这会返回> head(DistanceOutput, n=3) Source: local data frame [10 x 6] Name Quarter Sample X Y Distance (fctr) (dbl) (dbl) (dbl) (dbl) (dbl) 1 Bobby 1 1 27.82656 13.85830 NA 2 Bobby 1 2 26.32446 12.64722 1.929508 3 Bobby 1 3 29.68239 13.82739 3.559287，其结构如下：

dplyr

相反，我希望我的数据设置如下：

var mongoose = require('mongoose');
var Long = require("long");
	
	var UserSchema = new mongoose.Schema({
		id: Long(),
		name: String,
		completed: Long(),
		note: String,
		updated_at: { type: Date, default: Date.now },
	});

我如何正确设置group_by并在{{ session()->get('userinfo')->name }}内安排语句以正确反映我想要的输出？

谢谢。

Answer 1

我猜这是订单问题

DistanceOutput %>% 
         arrange(Name, Quarter, Sample) %>%
         head(3)
#   Name Quarter Sample        X        Y Distance
# <fctr>   <dbl>  <dbl>    <dbl>    <dbl>    <dbl>
#1  Bobby       1      1 28.40293 15.40195       NA
#2  Bobby       1      2 26.33676 14.32382 2.330544
#3  Bobby       1      3 28.60779 14.67457 2.297951

如何在dplyr中正确设置排列和分组？

1 个答案: