英文:
Use Value in Column as Upper Limit of Summation to Create a New Column
问题
我试图在一个R数据表中创建一个新列，该列对从另一个列中的值累加求和。这里有一个例子：
| x（现有列） | y（新列） |
|---|---|
|2|3|
|3|6|
|4|10|
|5|15|
在表的第一行中，我们通过对1到2进行求和（1+2=3）来得到y，在第二行中，我们对1到3进行求和（1+2+3=6），依此类推。在实际问题中，x中的值可以是任何整数（即它们不是有序的，也不可预测）。
我尝试了一些不同的方法，从非常天真的方法开始：
`dt[,y:=sum(c(1:x))]`，这不出奇地会产生关于仅使用了x的一些元素的警告，因为它（我相信）试图将x作为列使用，而不是在x的每一行中使用变量。我尝试使用`lapply`来处理每一行，但也无法使其正常工作。
显而易见的解决方案，我目前已经实现了，那就是循环遍历每一行，这样问题就变得很简单了。然而，我觉得一定有一个更加流畅的data.table解决方案存在。
英文:
I'm trying to create a new column in an R data.table that sums from 1 to the value in a different column. Here's an example:
| x (existing column) | y (new column) |
|---|---|
| 2 | 3 |
| 3 | 6 |
| 4 | 10 |
| 5 | 15 |
In the first row of the table we get y by summing 1 through 2 (1+2=3), in the second we sum 1 through 3 (1+2+3=6), etc. In the real problem the values in x can be any integer (i.e. they're not in order and not predictable).
I've tried a few different things, starting with the very naive approach:
dt[,y:=sum(c(1:x))] which, unsurprisingly, gives warnings about only using some elements of x, since it's (I believe) trying to use x as a column instead of using the variable in each row of x. I tried using lapply to work on each row, but I can't get that to work either.
The obvious solution, which I've implemented for now, is to loop through each row, in which case the problem is trivial. However, I feel like there must be a more streamlined data.table solution somewhere.
答案1
得分: 2
你正在尝试的是有效执行 1:(2:5)，而 : 需要每一侧都有一个单独的数字（因此它只采用第一个数字；2）。
以下是可能有效的替代方法：
dt[, y := sapply(x, \(y) sum(1:y))]
dt[, y := (x*(x+1L)) %/% 2L]
可重现的数据：
dt <- data.table(x = 2L:5L)
英文:
What you are trying to do is effectively 1:(2:5) while : is expecting a single number on each side (so it just takes the first; 2).
Here are alternatives that should work:
dt[, y := sapply(x, \(y) sum(1:y))]
dt[, y := (x*(x+1L)) %/% 2L]
Reproducible data:
dt <- data.table(x = 2L:5L)
答案2
得分: 0
A [tag:tidyverse] solution:
library(tidyverse)
df <- tibble(x = 2:5)
df %>%
mutate(y = map_dbl(x, ~sum(1:.x)))
# A tibble: 4 × 2
x y
<int> <dbl>
1 2 3
2 3 6
3 4 10
4 5 15
(Note: The code section has not been translated, only the surrounding text has been translated.)
英文:
A [tag:tidyverse] solution:
library(tidyverse)
df <- tibble(x = 2:5)
df %>%
mutate(y = map_dbl(x, ~sum(1:.x)))
# A tibble: 4 × 2
x y
<int> <dbl>
1 2 3
2 3 6
3 4 10
4 5 15
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