问题描述
以下是我正在运行的包列表、示例数据和脚本。下面是模式。您会注意到其中两个值大于 500，因此不符合架构。期望的结果将只考虑那些符合架构的（雇用少于 500 人）。当我在更大的数据集（不是下面的示例数据集）上运行它时，我得到的结果就像在底部找到的一样。简而言之，我将如何修改脚本，使其忽略大于 500 的条目，因此不返回 NA 的第五行？
library(dplyr)
library(data.table)
library(odbc)
library(DBI)
library(stringr)
firm <- c("firm1","firm2","firm3","firm4","firm5","firm6","firm7","firm8","firm9","firm10","firm11")
employment <- c(1,50,90,249,499,115,145,261,210,874,1140)
small <- c(1,1,3,4,2,NA,NA)
smbtest <- data.frame(firm,employment,small)
smbsummary2<-smbtest %>%
select(employment,small) %>%
group_by(small) %>%
summarise(employment = sum(employment),worksites = n(),.groups = 'drop') %>%
mutate(employment = cumsum(employment),worksites = cumsum(worksites))
smb1 >= 0 and <100
smb2 >= 0 and <150
smb3 >= 0 and <250
smb4 >= 0 and <500
smb employment worksites
1 1000 20
2 1500 22
3 2500 25
4 10000 29
5 25000 NA
解决方法
在这里我相信这会有所帮助
firm <- c("firm1","firm2","firm3","firm4","firm5","firm6","firm7","firm8","firm9","firm10","firm11")
employment <- c(1,50,90,249,499,115,145,261,210,874,1140)
small <- c(1,1,3,4,2,NA,NA)
smbtest <- data.frame(firm,employment,small)
smbtest %>%
select(employment,small) %>%
group_by(small) %>%
summarise(employment = sum(employment),worksites = n(),.groups = 'drop') %>%
mutate(employment = cumsum(employment),worksites = cumsum(worksites)) %>% drop_na() %>% filter(employment < 500)
我刚刚添加了两行语法
- “drop_na”
- "过滤器(就业