如何在R中总结得出小组的模式 [英] How to get the mode of a group in summarize in R

问题描述

我想比较来自两个不同索赔人的CPT代码的费用。两者都有面值和非面值的提供商。我正在使用 dplyr 和 modeest :: mlv ，但是它无法正常工作。以下是一些示例数据；

I want to compare costs of CPT codes from two different claims payers. Both have par and non par priced providers. I am using dplyr and modeest::mlv, but its not working out as anticipated. Heres some sample data;

source CPTCode ParNonPar Key         net_paid  PaidFreq seq
ABC   100       Y      ABC100Y  -341.00     6   1
ABC   100       Y      ABC100Y     0.00     2   2
ABC   100       Y      ABC100Y   341.00     6   3
XYZ   103       Y      XYZ103Y   740.28     1   1
XYZ   104       N      XYZ104N     0.00     2   1
XYZ   104       N      XYZ104N   401.82     1   2
XYZ   104       N      XYZ104N   726.18     1   3
XYZ   104       N      XYZ104N   893.00     1   4
XYZ   104       N      XYZ104N   928.20     2   5
XYZ   104       N      XYZ104N   940.00     2   6

和代码

str(data)
View(data)

## Expand frequency count to individual observations
n.times <- data$PaidAmounts
dataObs <- data[rep(seq_len(nrow(data)), n.times),]

## Calculate mean for each CPTCode (for mode use modeest library)
library(dplyr)
library(modeest)
dataSummary <- dataObs %>%
  group_by(ParNonPar, CPTCode) %>%
  summarise(mean = mean(net_paid),
            median=median(net_paid),
            mode = mlv(net_paid, method=mfv),
            total = sum(net_paid))
str(dataSummary)                     

我以为我可以在汇总函数中以均值和中位数加载最适度的值，但是这种表达方式会出错
as.character（x）中的错误：
无法将类型'closure'强制转换为类型为'character'的向量
如果没有mlv，我会得到这样的df，但是我想要的是在一行上获取付款方cpt的所有统计信息。我设想通过限制x和y分段在箱图中绘制图形，一旦我连续获得所需的东西

I thought I could load modeest in the summarize function with the mean and median, but this formulation errors out with Error in as.character(x) : cannot coerce type 'closure' to vector of type 'character' Without mlv I am getting a df like this, but what I want is to get all the stats for a payer cpt on one line. I envision graphing it in boxplots by limiting the x and y segments, once I get what I need on a row

这个答案是不足够的（我忘了得到付款人

the inadequate answer is this ( I forgot to get the payer name in here!)

ParNonPar   CPTCode mean          median(net_paid)  total
N           0513F   0.000000    0.000           0.00
N           0518F   0.000000    0.000           0.00 
N           10022   0.000000    0.000           0.00
N           10060   73.660000   90.120        294.64
N           10061   324.575000  340.500      1298.30
N           10081   312.000000  312.000       312.00

thanks very much for your time and effort.

推荐答案

您需要对代码进行一些更改为mlv工作。

You need to make a couple of changes to your code for mlv to work.

1. 方法（mfv）必须在引号（'mfv'）之内。这就是导致错误的原因。


2. 执行此操作后，由于mlv返回一个列表，因此必须将一个值提供给summarise（）。假设您需要模式（'M'），则从列表中选择该元素。

尝试：

dataSummary <- dataObs %>%
  group_by(ParNonPar, CPTCode) %>%
  summarise(mean = mean(net_paid), 
            meadian=median(net_paid), 
            mode = mlv(net_paid, method='mfv')[['M']], 
            total = sum(net_paid))

以获取：

> dataSummary
Source: local data frame [3 x 6]
Groups: ParNonPar

  ParNonPar CPTCode     mean meadian     mode   total
1         N     104 639.7111  893.00 622.7333 5757.40
2         Y     100   0.0000    0.00   0.0000    0.00
3         Y     103 740.2800  740.28 740.2800  740.28

希望帮助您前进。

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