根據R中另一列的值計算一列的值-有解無憂

使用資料框，我想創建一個新的，其中包含 Zip、Name 和一個名為 Count 的列，該列將包含每個 Zip 的名稱計數。

Zip<-c("123245","12345","123245","123456","123456","12345")
Name<-c("Bob","Bob","Bob","Jack","Jack","Mary")
df<-data.frame(Zip,Name)

library(dplyr)
df %>%
  group_by(Zip) %>%
  mutate(Name = cumsum(Name))

預期的

Zip Name Count
1 123245  Bob     2
2  12345  Bob     1
3  12345 Mary     1
4 123456 Jack     2

uj5u.com熱心網友回復：

我們可以使用的name引數count。

count基本上總結group_by和summarise：

library(dplyr)
df %>% 
  count(Zip, Name, name= "Count")

     Zip Name Count
1 123245  Bob     2
2  12345  Bob     1
3  12345 Mary     1
4 123456 Jack     2

uj5u.com熱心網友回復：

這能解決您的問題嗎？

Zip<-c("123245","12345","123245","123456","123456","12345")
Name<-c("Bob","Bob","Bob","Jack","Jack","Mary")
df<-data.frame(Zip,Name)

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
df %>%
  group_by(Zip, Name) %>%
  summarise(Count = n())
#> `summarise()` has grouped output by 'Zip'. You can override using the `.groups` argument.
#> # A tibble: 4 × 3
#> # Groups:   Zip [3]
#>   Zip    Name  Count
#>   <chr>  <chr> <int>
#> 1 123245 Bob       2
#> 2 12345  Bob       1
#> 3 12345  Mary      1
#> 4 123456 Jack      2

^{由reprex 包(v2.0.1)于 2021 年 12 月 22 日創建}

——

快速速度基準：

library(tidyverse)
library(microbenchmark)

Zip<-c("123245","12345","123245","123456","123456","12345")
Name<-c("Bob","Bob","Bob","Jack","Jack","Mary")
df<-data.frame(Zip,Name)

JM <- function(df){
  df %>%
  group_by(Zip, Name) %>%
  summarise(Count = n())
}
JM(df)
#> `summarise()` has grouped output by 'Zip'. You can override using the `.groups` argument.
#> # A tibble: 4 × 3
#> # Groups:   Zip [3]
#>   Zip    Name  Count
#>   <chr>  <chr> <int>
#> 1 123245 Bob       2
#> 2 12345  Bob       1
#> 3 12345  Mary      1
#> 4 123456 Jack      2

TarJae <- function(df){
  df %>% 
    count(Zip, Name, name= "Count")
}

TIC <- function(df){
  aggregate(cbind(Count = Zip) ~ Zip   Name, df, length)
}
TIC(df)
#>      Zip Name Count
#> 1 123245  Bob     2
#> 2  12345  Bob     1
#> 3 123456 Jack     2
#> 4  12345 Mary     1

res <- microbenchmark(JM(df), TIC(df), TarJae(df))
autoplot(res)
#> Coordinate system already present. Adding new coordinate system, which will replace the existing one.

根據R中另一列的值計算一列的值

^{由reprex 包(v2.0.1)于 2021 年 12 月 22 日創建}

uj5u.com熱心網友回復：

使用基本 R 選項 aggregte

> aggregate(cbind(Count = Zip) ~ Zip   Name, df, length)
     Zip Name Count
1 123245  Bob     2
2  12345  Bob     1
3 123456 Jack     2
4  12345 Mary     1

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標籤：r

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