选择的未定义列，无法XTFRM数据框架错误

发布于 2025-02-08 20:36:50 字数 718 浏览 2 评论 0原文

我正在尝试编写一个基于IQR检查异常值的代码，并将这些值更改为“ NA”。因此，我写了这篇文章：

dt <- rnorm(200) 
dg <- rnorm(200)
dh <- rnorm(200)

l <- c(1,3) #List of relevant columns

df <- data.frame(dt,dg,dh)

要检查列是否包含任何异常值并将其值更改为NA：

vector.is.empty <- function(x) return(length(x) ==0) 
#Checks for empty values in vector and returns booleans. 

for (i in 1:length(l)){
 IDX <- l[i]
 BP <- boxplot.stats(df[IDX])
 OutIDX <- which(df[IDX] %in% BP$out)
 if (vector.is.empty(OutIDX)==FALSE){
  for (u in 1:length(OutIDX)){
      IDX2 <- OutIDX[u]
      df[IDX2,IDX] <- NA
    }
  }
}

因此，当我运行此代码时，我会收到这些错误消息：

任何好的答案。但是我不确定为什么他们声称该列未指定。这里有线索吗？

原文

I am trying to write a code that checks for outliers based on IQR and change those respective values to "NA". So I wrote this:

dt <- rnorm(200) 
dg <- rnorm(200)
dh <- rnorm(200)

l <- c(1,3) #List of relevant columns

df <- data.frame(dt,dg,dh)

To check if the column contains any outliers and change their value to NA:

vector.is.empty <- function(x) return(length(x) ==0) 
#Checks for empty values in vector and returns booleans. 

for (i in 1:length(l)){
 IDX <- l[i]
 BP <- boxplot.stats(df[IDX])
 OutIDX <- which(df[IDX] %in% BP$out)
 if (vector.is.empty(OutIDX)==FALSE){
  for (u in 1:length(OutIDX)){
      IDX2 <- OutIDX[u]
      df[IDX2,IDX] <- NA
    }
  }
}

So, when I run this code, I get these error messages:

I've tried to search online for any good answers. but I'm not sure why they claim that the column is unspecified. Any clues here?

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忘你却要生生世世 2025-02-15 20:36:51

我会做类似的事情以替换异常值：

# Set a seed (to make the example reproducible)
  set.seed(31415)
# Generate the data.frame
  df <- data.frame(dt = rnorm(100), dg = rnorm(100), dh = rnorm(100))
# A list to save the result of boxplot.stats()
  l <- list()
  for (i in 1:ncol(df)){
    l[[i]] <- boxplot.stats(df[,i])
    df[which(df[,i]==l[[i]]$out),i] <- NA
  }

# Which values have been replaced?
  lapply(l, function(x) x$out)

I would do something like that in order to replace the outliers:

# Set a seed (to make the example reproducible)
  set.seed(31415)
# Generate the data.frame
  df <- data.frame(dt = rnorm(100), dg = rnorm(100), dh = rnorm(100))
# A list to save the result of boxplot.stats()
  l <- list()
  for (i in 1:ncol(df)){
    l[[i]] <- boxplot.stats(df[,i])
    df[which(df[,i]==l[[i]]$out),i] <- NA
  }

# Which values have been replaced?
  lapply(l, function(x) x$out)

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