如何使用随机选择创建新的VAR？

发布于 2025-02-12 07:59:33 字数 836 浏览 1 评论 0原文

使用dplyr，我想创建一个新变量new_regsiege，具有以下条件：

对于每行，如果regsiege ==“ xx”，则“ xx” ＆gt; 0然后new_regsiege = regsiege

如果regsiege ==“ xx”和nbeta_regxx = 0，然后new_regsiege是在不是null的regsiege中随机选择的Regsiege之一。

这是我的例子：

mydf <- data.frame(
  regsiege = c("11","24","93"),
  nbeta_reg11 = c(0,1,0),
  nbeta_reg24 = c(1,1,0),
  nbeta_reg93 = c(1,1,1)
)

# Desired output
regsiege nbeta_reg11 nbeta_reg24 nbeta_reg93 new_regsiege
      11           0           1           1           93 (could be also "24")
      24           1           1           1           24
      93           0           0           1           93

我开始这样开始：

mydf %>% 
  rowwise()
  mutate(
    new_regsiege = if_else(...
  )

原文

With dplyr, I would like to create a new variable new_regsiege with the following conditions:

For each line and "XX" if regsiege=="XX" and nbeta_regXX>0 then new_regsiege=regsiege

if regsiege=="XX" and nbeta_regXX=0 then new_regsiege is one of the regsiege randomly chosen among those which are not null.

Here's my example :

mydf <- data.frame(
  regsiege = c("11","24","93"),
  nbeta_reg11 = c(0,1,0),
  nbeta_reg24 = c(1,1,0),
  nbeta_reg93 = c(1,1,1)
)

# Desired output
regsiege nbeta_reg11 nbeta_reg24 nbeta_reg93 new_regsiege
      11           0           1           1           93 (could be also "24")
      24           1           1           1           24
      93           0           0           1           93

I started like this :

mydf %>% 
  rowwise()
  mutate(
    new_regsiege = if_else(...
  )

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傻比既视感 2025-02-19 07:59:33

你可以尝试

library(tidyverse)

mydf %>%
  pivot_longer(-1, names_prefix = "nbeta_reg") %>%
  group_by(regsiege) %>%
  summarise(new_regsiege = if(value[regsiege == name] > 0) regsiege[1]
                           else sample(name[value > 0], 1)) %>%
  left_join(mydf, ., by = "regsiege")

#   regsiege nbeta_reg11 nbeta_reg24 nbeta_reg93 new_regsiege
# 1       11           0           1           1           93
# 2       24           1           1           1           24
# 3       93           0           0           1           93

You could try

library(tidyverse)

mydf %>%
  pivot_longer(-1, names_prefix = "nbeta_reg") %>%
  group_by(regsiege) %>%
  summarise(new_regsiege = if(value[regsiege == name] > 0) regsiege[1]
                           else sample(name[value > 0], 1)) %>%
  left_join(mydf, ., by = "regsiege")

#   regsiege nbeta_reg11 nbeta_reg24 nbeta_reg93 new_regsiege
# 1       11           0           1           1           93
# 2       24           1           1           1           24
# 3       93           0           0           1           93

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芸娘子的小脾气 2025-02-19 07:59:33

最简单的解决方案将使用一个循环：

for (i in seq_len(nrow(mydf))) {
  cur_regsiege  <- mydf[i, "regsiege"]
  same          <- mydf[i, paste0("nbeta_reg", cur_regsiege)]
  mydf[i, "new_regsiege"] <- if (same) cur_regsiege else sample(mydf[-i, "regsiege"], 1L)
}

#   regsiege nbeta_reg11 nbeta_reg24 nbeta_reg93 new_regsiege
# 1       11           0           1           1           93
# 2       24           1           1           1           24
# 3       93           0           0           1           93

The simplest solution would use a loop:

for (i in seq_len(nrow(mydf))) {
  cur_regsiege  <- mydf[i, "regsiege"]
  same          <- mydf[i, paste0("nbeta_reg", cur_regsiege)]
  mydf[i, "new_regsiege"] <- if (same) cur_regsiege else sample(mydf[-i, "regsiege"], 1L)
}

#   regsiege nbeta_reg11 nbeta_reg24 nbeta_reg93 new_regsiege
# 1       11           0           1           1           93
# 2       24           1           1           1           24
# 3       93           0           0           1           93

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