如何创建一个对重复行求和的列，然后仅删除 R 中的一个重复项？

Question

我有一个非常庞大的数据集，我正在寻找最简单（也是最快）的方法来创建一个列，该列对一个特定列的值求和，然后继续只留下一个重复值。

我的数据集如下所示：

data <- data.frame(DATE_INTER = c("2015-05-29", "2013-12-13", "2009-09-08"),
                   DATE_SAIDA = c("2015-06-10", "2013-12-15", "2009-10-20"),
                   GRUPO_AIH = c("09081997", "13122006", "13122006"),
                   DIAS_PERMANENCIA = c(12, 2, 42))

我需要使用列“GRUPO_AIH”来检查重复项。我的最终输出将是这样的：

我已经尝试过了，但是它花费的时间太长，而且在完成之后，我什至无法使用 dplyr 过滤 R 停止工作的任何内容。

data <- data %>%
  group_by(GRUPO_AIH) %>%
  mutate(DIAS_PERMANENCIA2 = sum(DIAS_PERMANENCIA))

有什么建议吗？

Answer 1

答案在这里。只是一个观察，在您提供的数据集示例中，GRUPO_AIH 变量中实际上没有任何重复值，因此我更改为 GRUPO_AIH = c("09081997", "13122006", "13122006"),

data %>%
  group_by(GRUPO_AIH) %>%
  mutate(DIAS_PERMANENCIA = sum(DIAS_PERMANENCIA)) %>%
  filter(duplicated(GRUPO_AIH) == FALSE)




DATE_INTER DATE_SAIDA GRUPO_AIH DIAS_PERMANENCIA
  <chr>      <chr>      <chr>                <dbl>
1 2015-05-29 2015-06-10 09081997                12
2 2013-12-13 2013-12-15 13122006                44

OBS：também sou sanitarista atuando com dados na vigilância kk

Answer 2

如果您有一个“非常大的数据集”（数百万行），也许这会是最快的：

library(data.table)
data <- data.frame(DATE_INTER = c("2015-05-29", "2013-12-13", "2009-09-08"),
                   DATE_SAIDA = c("2015-06-10", "2013-12-15", "2009-10-20"),
                   GRUPO_AIH = c("09081997", "13122206", "13122206"),
                   DIAS_PERMANENCIA = c(12, 2, 42))

data_dt <- setDT(data)
setkey(data_dt, GRUPO_AIH)

data_dt[, DIAS_PERMANENCIA := sum(DIAS_PERMANENCIA), by = "GRUPO_AIH"]
data_final <- as.data.frame(data_dt[!duplicated(data_dt, by = "GRUPO_AIH")])
data_final
#>   DATE_INTER DATE_SAIDA GRUPO_AIH DIAS_PERMANENCIA
#> 1 2015-05-29 2015-06-10  09081997               12
#> 2 2013-12-13 2013-12-15  13122206               44

^{由 reprex package (v2.0.1)}

于 2022-05-31 创建

基准测试：

#install.packages("data.table")
#install.packages("dplyr")
#install.packages("microbenchmark")

library(microbenchmark)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(ggplot2)

data <- data.frame(DATE_INTER = rep(c("2015-05-29", "2013-12-13", "2009-09-08"), times = 10e5),
                   DATE_SAIDA = rep(c("2015-06-10", "2013-12-15", "2009-10-20"), times = 10e5),
                   GRUPO_AIH = rep(c("09081997", "13122206", "13122206"), times = 10e5),
                   DIAS_PERMANENCIA = rep(c(12, 2, 42), times = 10e5))

dplyr_func <- function(data){
  data_final <- data %>%
    dplyr::group_by(GRUPO_AIH) %>%
    dplyr::mutate(DIAS_PERMANENCIA = sum(DIAS_PERMANENCIA)) %>%
    dplyr::filter(duplicated(GRUPO_AIH) == FALSE)
  return(data_final)
}

dt_func <- function(data){
  data_dt <- data.table::setDT(data)
  data.table::setkey(data_dt, GRUPO_AIH)
  data_dt[, DIAS_PERMANENCIA := sum(DIAS_PERMANENCIA), by = "GRUPO_AIH"]
  data_final <- as.data.frame(data_dt[!duplicated(data_dt, by = "GRUPO_AIH")])
  return(data_final)
}

dplyr::all_equal(dplyr_func(data), dt_func(data))
#> [1] TRUE

res <- microbenchmark(dplyr_func(data), dt_func(data), times = 4)
autoplot(res)
#> Coordinate system already present. Adding new coordinate system, which will replace the existing one.

# The difference in speed will likely become more pronounced as the size of the data increases
data <- data.frame(DATE_INTER = rep(c("2015-05-29", "2013-12-13", "2009-09-08"), times = 10e6),
                   DATE_SAIDA = rep(c("2015-06-10", "2013-12-15", "2009-10-20"), times = 10e6),
                   GRUPO_AIH = rep(c("09081997", "13122206", "13122206"), times = 10e6),
                   DIAS_PERMANENCIA = rep(c(12, 2, 42), times = 10e6))

dplyr_func <- function(data){
  data_final <- data %>%
    dplyr::group_by(GRUPO_AIH) %>%
    dplyr::mutate(DIAS_PERMANENCIA = sum(DIAS_PERMANENCIA)) %>%
    dplyr::filter(duplicated(GRUPO_AIH) == FALSE)
  return(data_final)
}

dt_func <- function(data){
  data_dt <- data.table::setDT(data)
  data.table::setkey(data_dt, GRUPO_AIH)
  data_dt[, DIAS_PERMANENCIA := sum(DIAS_PERMANENCIA), by = "GRUPO_AIH"]
  data_final <- as.data.frame(data_dt[!duplicated(data_dt, by = "GRUPO_AIH")])
  return(data_final)
}

res <- microbenchmark(dplyr_func(data), dt_func(data), times = 2)
autoplot(res)
#> Coordinate system already present. Adding new coordinate system, which will replace the existing one.

由 reprex 包 (v2.0.1) 创建于 2022-05-31

如何创建一个对重复行求和的列，然后仅删除 R 中的一个重复项？

How to create a column that sums duplicated rows and then delete only one of the duplicates in R?

r

duplicates

dplyr