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我正在编写一个非常简单的 if else 循环来创建一个新变量，该变量将另一个变量分成四分位数。这似乎是一个非常简单的过程，但是循环将我的所有数据分组到中位数和第三四分位数（这违反了四分位数的定义）。

这是我的数据结构：

> str(tmp)
Classes ‘tbl_df’, ‘tbl’ and 'data.frame':   435 obs. of  12 variables:
 $ CD112FP             : chr  "01" "02" "03" "04" ...
 $ State               : chr  "ALABAMA" "ALABAMA" "ALABAMA" "ALABAMA" ...
 $ Year                : num  2011 2011 2011 2011 2011 ...
 $ Alignment           : num  0 0 0 0 0 0 1 0 0 0 ...
 $ State_Aligned       : num  0 0 0 0 0 0 0 1 0 0 ...
 $ PercentFunding      : num  0.0658 0.29 0.6764 0.0174 0.047 ...
 $ fips                : chr  "01" "01" "01" "01" ...
 $ ssa                 : int  1 1 1 1 1 1 1 NA 3 3 ...
 $ region              : int  3 3 3 3 3 3 3 NA 4 4 ...
 $ division            : int  6 6 6 6 6 6 6 NA 8 8 ...
 $ abb                 : chr  "AL" "AL" "AL" "AL" ...
 $ PercentFundingBinned: chr  "0.0625-0.1799" "0.0625-0.1799" "0.0625-0.1799" "0.0625-0.1799" ...

这是我的数据的负责人：

 head(tmp)
# A tibble: 6 x 12
  CD112FP State    Year Alignment State_Aligned PercentFunding fips    ssa region division abb   PercentFundingBinned
  <chr>   <chr>   <dbl>     <dbl>         <dbl>          <dbl> <chr> <int>  <int>    <int> <chr> <chr>               
1 01      ALABAMA  2011         0             0         0.0658 01        1      3        6 AL    0.0625-0.1799       
2 02      ALABAMA  2011         0             0         0.290  01        1      3        6 AL    0.0625-0.1799       
3 03      ALABAMA  2011         0             0         0.676  01        1      3        6 AL    0.0625-0.1799       
4 04      ALABAMA  2011         0             0         0.0174 01        1      3        6 AL    0.0625-0.1799       
5 05      ALABAMA  2011         0             0         0.0470 01        1      3        6 AL    0.0625-0.1799       
6 06      ALABAMA  2011         0             0         0.0440 01        1      3        6 AL    0.0625-0.1799

我正在使用以下 if else 循环：

  tmp$PercentFundingBinned <- NULL
  if (tmp$PercentFunding >= quantile(tmp$PercentFunding, 0.75)) {
    tmp$PercentFundingBinned <- paste0(round(quantile(tmp$PercentFunding, 0.75), 4), "-",
                                       round(max(tmp$PercentFundingBinned), 4))
  } else if (tmp$PercentFunding >= median(tmp$PercentFunding)){
    tmp$PercentFundingBinned <- paste0(round(median(tmp$PercentFunding),4), "-", 
                                       round(quantile(tmp$PercentFunding, 0.75),4))
  } else if (tmp$PercentFunding >= quantile(tmp$PercentFunding, 0.25)){
    tmp$PercentFundingBinned <- paste0(round(quantile(tmp$PercentFunding, 0.25),4), "-", 
                                       round(median(tmp$PercentFunding),4))
  } else {
    tmp$PercentFundingBinned <- paste0(round(min(tmp$PercentFunding),4), "-", 
                                             round(quantile(tmp$PercentFunding, 0.25),4))
  }

它返回以下类别：

unique(tmp$PercentFundingBinned)
[1] "0.0625-0.1799"

不知道该做什么或如何适应它。这似乎应该是一个非常简单的过程。任何建议都有帮助，谢谢！

4

2 回答 2

2

我建议你根本不需要ifelse。

tmp <- read.table(header=TRUE, stringsAsFactors=FALSE, text="
  CD112FP State    Year Alignment State_Aligned PercentFunding fips    ssa region division abb   PercentFundingBinned
1 01      ALABAMA  2011         0             0         0.0658 01        1      3        6 AL    0.0625-0.1799       
2 02      ALABAMA  2011         0             0         0.290  01        1      3        6 AL    0.0625-0.1799       
3 03      ALABAMA  2011         0             0         0.676  01        1      3        6 AL    0.0625-0.1799       
4 04      ALABAMA  2011         0             0         0.0174 01        1      3        6 AL    0.0625-0.1799       
5 05      ALABAMA  2011         0             0         0.0470 01        1      3        6 AL    0.0625-0.1799       
6 06      ALABAMA  2011         0             0         0.0440 01        1      3        6 AL    0.0625-0.1799       ")
quants <- quantile(tmp$PercentFunding, c(0, 0.25, 0.5, 0.75, 1))
quants
#      0%     25%     50%     75%    100% 
# 0.01740 0.04475 0.05640 0.23395 0.67600 
cuts <- cut(tmp$PercentFunding,
            quants, include.lowest = TRUE, dig.lab = 4,
            labels = sprintf("%0.04f-%0.04f", head(quants, n = -1), quants[-1]))
cuts
# [1] 0.0564-0.2339 0.2339-0.6760 0.2339-0.6760 0.0174-0.0447 0.0447-0.0564 0.0174-0.0447
# Levels: 0.0174-0.0447 0.0447-0.0564 0.0564-0.2339 0.2339-0.6760

当然，这是一个factor, 但as.character如果需要，可以很容易地转换。

tmp$PercentFundingBinned <- as.character(cuts)
于 2020-03-13T21:50:34.040 回答
0

我强烈建议您始终注意警告。

处理向量时不应使用if，因为如警告中所示，只会使用第一个元素：

> if(c(TRUE, FALSE)) 1 else 2
[1] 1
Warning message:
In if (c(TRUE, FALSE)) 1 else 2 :
  the condition has length > 1 and only the first element will be used
> if(c(FALSE, TRUE)) 1 else 2
[1] 2
Warning message:
In if (c(FALSE, TRUE)) 1 else 2 :
  the condition has length > 1 and only the first element will be used

在您的情况下发生的情况是：第一个值为 0.0658，因此 if 确定它在 0.0625-0.1799 的 bin 中。而且因为您为向量分配了一个值，所以该值被分配给向量的每个元素。

相反，您可以使用ifelse：

tmp$PercentFundingBinned <- ifelse (
  tmp$PercentFunding >= quantile(tmp$PercentFunding, 0.75) , 
  paste0(round(quantile(tmp$PercentFunding, 0.75), 4), "-",
         round(max(tmp$PercentFundingBinned), 4)),
  ifelse(tmp$PercentFunding >= median(tmp$PercentFunding),
         paste0(round(median(tmp$PercentFunding),4), "-",
                round(quantile(tmp$PercentFunding, 0.75),4)),
         ifelse(tmp$PercentFunding >= quantile(tmp$PercentFunding, 0.25),
                paste0(round(quantile(tmp$PercentFunding, 0.25),4), "-", 
                       round(median(tmp$PercentFunding),4)), 
                paste0(round(min(tmp$PercentFunding),4), "-", 
                       round(quantile(tmp$PercentFunding, 0.25),4))
         )
    )
)
于 2020-03-13T21:31:06.137 回答