英文:
Assigning phases to stock prices in R
问题
| Date | Price UP | Price Down | PhaseIndicator |
|---|---|---|---|
| 2023-01-01 | NA | NA | |
| 2023-01-02 | 10 | NA | 第 1 阶段 |
| 2023-01-03 | NA | NA | 第 1 阶段 |
| 2023-01-04 | NA | 4 | 第 1 阶段 |
| 2023-01-05 | NA | 3 | |
| 2023-01-06 | 10 | NA | 第 2 阶段 |
| 2023-01-07 | NA | 2 | 第 2 阶段 |
英文:
I have an R dataframe that looks something like this:
| Date | Price UP | Price Down |
|---|---|---|
| 2023-01-01 | NA | NA |
| 2023-01-02 | 10 | NA |
| 2023-01-03 | NA | NA |
| 2023-01-04 | NA | 4 |
| 2023-01-05 | NA | 3 |
| 2023-01-06 | 10 | NA |
| 2023-01-07 | NA | 2 |
I tried using for loop to assign 'Phase numbers' every time the price goes up and then comes down. For example if the price UP is 10 and the next price down after that is 4, then the dates between them are Phase 1, and so on we mark Phase 2, 3, ...n.
Can we have a dplyr friendly way to get the same result?
The final output should look something like this:
| Date | Price UP | Price Down | PhaseIndicator |
|---|---|---|---|
| 2023-01-01 | NA | NA | |
| 2023-01-02 | 10 | NA | Phase 1 |
| 2023-01-03 | NA | NA | Phase 1 |
| 2023-01-04 | NA | 4 | Phase 1 |
| 2023-01-05 | NA | 3 | |
| 2023-01-06 | 10 | NA | Phase 2 |
| 2023-01-07 | NA | 2 | Phase 2 |
答案1
得分: 0
这是您提供的R代码的翻译结果：
这是您提供的R代码的翻译结果：
```R
library(dplyr)
library(tidyr) # 为了使用fill函数，需要加载tidyr库
df = data.frame(date = 1:7, up = c(NA, 10, NA, NA, NA, 10, NA), down = c(NA, NA, NA, 4, 3, NA, 2))
df
date up down
1 1 NA NA
2 2 10 NA
3 3 NA NA
4 4 NA 4
5 5 NA 3
6 6 10 NA
7 7 NA 2
在这里，阶段号由价格上涨的次数确定，使用row_number(up > 0)。
使用fill()函数，阶段号（nup）被传递到下一个值。
df %>%
mutate(nup = row_number(up > 0)) %>%
fill(nup) %>%
mutate(phase_start = ifelse(!is.na(nup), paste0("pahase ", nup), NA))
date up down nup phase_start
1 1 NA NA NA <NA>
2 2 10 NA 1 pahase 1
3 3 NA NA 1 pahase 1
4 4 NA 4 1 pahase 1
5 5 NA 3 1 pahase 1
6 6 10 NA 2 pahase 2
7 7 NA 2 2 pahase 2
英文:
here my proposal tell me if it corresponds
library(dplyr)
library(tidyr) # you need tidyr for the fill function
df=data.frame(date = 1:7,up=c(NA,10,NA,NA,NA,10,NA),down=c(NA,NA,NA,4,3,NA,2))
df
date up down
1 1 NA NA
2 2 10 NA
3 3 NA NA
4 4 NA 4
5 5 NA 3
6 6 10 NA
7 7 NA 2
here the phases number is determined by the number of times the price go up row_number(up>0)
with fill() the phase number (nup) is carried forward to the next value
df%>%
mutate(nup=row_number(up>0))%>%
fill(nup)%>%
mutate(phase_start = ifelse(!is.na(nup),paste0("pahase ",nup),NA))
date up down nup phase_start
1 1 NA NA NA <NA>
2 2 10 NA 1 pahase 1
3 3 NA NA 1 pahase 1
4 4 NA 4 1 pahase 1
5 5 NA 3 1 pahase 1
6 6 10 NA 2 pahase 2
7 7 NA 2 2 pahase 2
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