将总计添加到数据框

Question

我想将总计添加到我的数据框中，但遇到了困难，因为数据非常混乱（一如既往！） - 有些列是文本，有些是日期，有些是数字。我无法发布实际数据，因为它很敏感，但我将展示一个具有代表性的示例，它是相同的结构（下面 - 所需的列是黄色的。我一直在尝试使用 dplyr 和管道来执行此操作，但由于以下原因遇到了问题文字和数字的混合......

数据：

date <- c("17/08/2020", "17/08/2020", "17/08/2020", "17/08/2020","18/08/2020", "18/08/2020", "18/08/2020", "18/08/2020")

type <- c("type A", "type B", "type A", "type B","type A", "type B","type A", "type B")

location <- c("USA","USA","India","India","USA","USA","India","India")

value <- c("10","10","frak","frak","15","15","open","open")

df <- data.frame(date, type, location, value)

基本上，我需要按日期、类型和位置汇总。 enter image description here

Answer 1

不确定这是否是你所追求的。

df %>%
  group_by(date, type = "total_type", location) %>%
  summarise("value" = sum(as.numeric(value), na.rm = F)) %>%
  mutate(value = as.character(value)) %>%
  bind_rows(df)

# A tibble: 12 x 4
# Groups:   date, type [6]
   date       type       location value
   <chr>      <chr>      <chr>    <chr>
 1 17/08/2020 total_type India    NA   
 2 17/08/2020 total_type USA      20   
 3 18/08/2020 total_type India    NA   
 4 18/08/2020 total_type USA      30   
 5 17/08/2020 type A     USA      10   
 6 17/08/2020 type B     USA      10   
 7 17/08/2020 type A     India    frak 
 8 17/08/2020 type B     India    frak 
 9 18/08/2020 type A     USA      15   
10 18/08/2020 type B     USA      15   
11 18/08/2020 type A     India    open 
12 18/08/2020 type B     India    open 

除value 之外的所有列分组会重现您的原始表，并且在您的图像中汇总行的类型 = total_type。另一方面，您在图像中的所有汇总行都有位置USA，这也没有意义，所以我就让它保持原样。

Answer 2

我会建议下一种方法，它也与@Humpelstielzchen 提出的方法接近，与您在图像中显示的接近：

library(dplyr)

df %>% bind_rows(df %>% group_by(date,location) %>%
                   mutate(value=as.numeric(value)) %>% 
                   summarise(value=sum(value,na.rm=F)) %>%
                   mutate(type='total type',value=as.character(value)))

输出：

         date       type location value
1  17/08/2020     type A      USA    10
2  17/08/2020     type B      USA    10
3  17/08/2020     type A    India  frak
4  17/08/2020     type B    India  frak
5  18/08/2020     type A      USA    15
6  18/08/2020     type B      USA    15
7  18/08/2020     type A    India  open
8  18/08/2020     type B    India  open
9  17/08/2020 total type    India  <NA>
10 17/08/2020 total type      USA    20
11 18/08/2020 total type    India  <NA>
12 18/08/2020 total type      USA    30

更新：由于 OP 的包版本问题，这里可以使用一种方法：

library(dplyr)
#Data
date <- c("17/08/2020", "17/08/2020", "17/08/2020", "17/08/2020","18/08/2020", "18/08/2020", "18/08/2020", "18/08/2020")

type <- c("type A", "type B", "type A", "type B","type A", "type B","type A", "type B")

location <- c("USA","USA","India","India","USA","USA","India","India")

value <- c("10","10","frak","frak","15","15","open","open")

df <- data.frame(date, type, location, value,stringsAsFactors = F)
#Mutate for summary
df1 <- df %>% group_by(date,location) %>%
  mutate(value=as.numeric(value)) %>% 
  summarise(value=sum(value,na.rm=F)) %>%
  mutate(type='total type') %>% ungroup()
df1$value <- as.character(df1$value)
#Bind
df2 <- rbind(df,df1)

输出：

         date       type location value
1  17/08/2020     type A      USA    10
2  17/08/2020     type B      USA    10
3  17/08/2020     type A    India  frak
4  17/08/2020     type B    India  frak
5  18/08/2020     type A      USA    15
6  18/08/2020     type B      USA    15
7  18/08/2020     type A    India  open
8  18/08/2020     type B    India  open
9  17/08/2020 total type    India  <NA>
10 17/08/2020 total type      USA    20
11 18/08/2020 total type    India  <NA>
12 18/08/2020 total type      USA    30