Question

我有两个csv文件。

一个文件列出员工离职的时间和原因。

EmployeeID,Department,Separation_Type,Separation_Date,FYFQ    
119549,Sales,Retirement,09/30/2013  
2629053,Sales,Termination,09/30/2013  
120395,Sales,Retirement,11/01/2013  
122450,Sales,Transfer,11/30/2013  
123962,Sales,Transfer,11/30/2013  
1041054,Sales,Resignation,12/01/2013  
990962,Sales,Retirement,12/14/2013  
135396,Sales,Retirement,01/11/2014

另一个文件是查找表，显示每个财政季度的开始和结束日期：

FYFQ,Start,End  
FY2014FQ1,10/1/2013,12/31/2013   
FY2014FQ2,1/1/2014,3/31/2014  
FY2014FQ3,4/1/2014,6/30/2014  
FY2014FQ4,7/1/2014,9/30/2014  
FY2015FQ1,10/1/2014,12/31/2014  
FY2015FQ2,1/1/2015,3/31/2015

我希望R找到Separation_Date发生的FYFQ并将其打印到数据的第四列。

输入：

Separations.csv:   
>EmployeeID,Department,Separation_Type,Separation_Date,FYFQ       
>990962,Sales,Retirement,12/14/2013  
>135396,Sales,Retirement,01/11/2014

FiscalQuarterDates.csv：

>FYFQ,Start,End  
>FY2013FQ4,7/1/2013,9/30/2013   
>FY2014FQ1,10/1/2013,12/31/2013  
>FY2014FQ2,1/1/2014,3/31/2014

所需的输出：
Output.csv：

>EmployeeID,Department,Separation_Type,Separation_Date,FYFQ      
>990962,Sales,Retirement,12/14/2013,FY2014FQ1
>135396,Sales,Retirement,01/11/2014,FY2014FQ2

我假设有一些函数可以遍历FiscalQuarterDates.csv并评估每个分离日期是否在FYFQ中，但我不确定。

有关最佳方法的任何想法吗？

这是有效的。

#read in csv and declare th3 4th column a date
separations <- read.csv(file="Separations_DummyData.csv", head=TRUE,sep=",",colClasses=c(NA,NA,NA,"Date"))


#Use the zoo package (I installed it) to convert separation_date to quarter type and then set the quarter back by 1/4. Then construct the variable with FYyFQq. 
library(zoo)
separations$FYFQ <- format(as.yearqtr(separations$Separation_Date, "%m/%d/%Y") + 1/4, "FY%YFQ%q")

#Write out this to CSV in working directory.
write.csv(separations, file = "sepscomplete.csv", row.names = FALSE)

Answer 1

你真的不需要第二个数据帧：一个简单的函数可以解决这个问题：

yr<-with(firstdf,as.numeric(substr(Seperation_Date,7,10)))
mth<-with(firstdf,as.numeric(substr(Seperation_Date,1,2)))


    firstdf$FYFQ<-with(firstdf,
ifelse(mth<=3,paste0("FY",yr,"FQ2"),
ifelse(mth>3 & mth<=6,paste0("FY",yr,"FQ3"),
ifelse(mth>7 & mth<=9,paste0("FY",yr,"FQ4"),
paste0("FY",yr+1,"FQ1")
))))

Answer 2

将每个日期转换为"yearqtr"类（来自动物园包）并添加1/4以将其转移到下一个日历季度。然后使用write.csv：

将其写出来

library(zoo)
DF$FYFQ <- format(as.yearqtr(DF$Separation_Date, "%m/%d/%Y") + 1/4, "FY%YFQ%q")

，并提供：

> write.csv(DF, file = stdout(), row.names = FALSE)
"EmployeeID","Department","Separation_Type","Separation_Date","FYFQ"
990962,"Sales","Retirement","12/14/2013","FY2014FQ1"
135396,"Sales","Retirement","01/11/2014","FY2014FQ2"

注意：

1）如果FYFQ不必完全采用所示格式，则可将其简化为：

DF$FYFQ <- as.yearqtr(DF$Separation_Date, "%m/%d/%Y") + 1/4

2）不使用问题中列出的第二个输入文件。

3）我们将此用作输入数据：

Lines <- "EmployeeID,Department,Separation_Type,Separation_Date,FYFQ 990962,Sales,Retirement,12/14/2013 135396,Sales,Retirement,01/11/2014" DF <- read.csv(text = Lines)

4）已修复，以便生成已移位的日历季度。

Answer 3

这个答案的文字只是另一个答案的副本，所以它已被移到了这个问题上。

用R来比较日期

3 个答案: