合并相同的名称并获取支持数据的总和 - Reprex
Merge Same Names and Get Sum of Supporting Data - Reprex
我有一个包含多次列出的客户名称的数据集。我希望在获得支持变量的总和的同时按月合并相同的客户名称。我喜欢使用 dplyr,但在求和支持变量时遇到了问题(例如 dep_delay & arr_delay)。我在下面使用了一个代表,其中承运人充当客户名称。感谢您花时间看这个例子!
理想情况下输出应该是这样的:
运营商/月/dep_delay/arr_delay
AA / 1 / 3412 / 12234
UA/1/1517/2594
AA / 1 / 12342 / 1231
UA / 1 / 121 / 1234
#代码如下
library(tidyverse)
library(readr)
library(lubridate)
library(nycflights13)
flights_updated <- flights[,c(10,2,6,9)]
flights_updated <- group_by(flights_updated, carrier, month) %>%
summarise (dep_delay = sum(dep_delay), arr_delay = sum(arr_delay))
我也试过这个作为替代品:
我试过下面几行代码也无济于事:
flights_updated <- flights_updated %>% group_by(carrier, month) %>% summarise_at(vars(dep_delay, arr_delay), sum)
aggregate(cbind(dep_delay, arr_delay) ~ carrier + month, data = flights_updated, sum, na.rm = TRUE)
在等待周末的指导后,我能够从@Talat 找到答案,这有助于提供所需的指导。 How to sum a variable by group
#Load packages
library(tidyverse)
library(dplyr)
library(readr)
library(lubridate)
library(nycflights13)
flights_updated <- flights[,c(10,2,6,9)]
flights_updated <- flights_updated %>%
group_by(carrier, month) %>%
summarise(dep_delay = sum(dep_delay), arr_delay = sum(arr_delay))
flights_updated
我有一个包含多次列出的客户名称的数据集。我希望在获得支持变量的总和的同时按月合并相同的客户名称。我喜欢使用 dplyr,但在求和支持变量时遇到了问题(例如 dep_delay & arr_delay)。我在下面使用了一个代表,其中承运人充当客户名称。感谢您花时间看这个例子!
理想情况下输出应该是这样的:
运营商/月/dep_delay/arr_delay
AA / 1 / 3412 / 12234
UA/1/1517/2594
AA / 1 / 12342 / 1231
UA / 1 / 121 / 1234
#代码如下
library(tidyverse)
library(readr)
library(lubridate)
library(nycflights13)
flights_updated <- flights[,c(10,2,6,9)]
flights_updated <- group_by(flights_updated, carrier, month) %>%
summarise (dep_delay = sum(dep_delay), arr_delay = sum(arr_delay))
我也试过这个作为替代品:
我试过下面几行代码也无济于事:
flights_updated <- flights_updated %>% group_by(carrier, month) %>% summarise_at(vars(dep_delay, arr_delay), sum)
aggregate(cbind(dep_delay, arr_delay) ~ carrier + month, data = flights_updated, sum, na.rm = TRUE)
在等待周末的指导后,我能够从@Talat 找到答案,这有助于提供所需的指导。 How to sum a variable by group
#Load packages
library(tidyverse)
library(dplyr)
library(readr)
library(lubridate)
library(nycflights13)
flights_updated <- flights[,c(10,2,6,9)]
flights_updated <- flights_updated %>%
group_by(carrier, month) %>%
summarise(dep_delay = sum(dep_delay), arr_delay = sum(arr_delay))
flights_updated