R编码：如何仅使用4个完整的四分之一数据来保存记录，以及如何在多个条件下获取条件和

Question

I have a dataframe with company quarterly data, and I have two questions:

1: How can I keep records for only those companies with four quarters of data (as companies sometimes appear with 1, 2 or 3 quarters of data but I need 4 quarters for each company across the entire dataframe)

2: Because I have quarterly data, I would like to take the annual average or sum (based on variable type) across all four quarters given 2 conditions: year and company.

For instance, Company i in 1984 would have an average inventory value and total revenue, say I1984 and REV1984 respectively, based on four distinct quarterly values. I am currently using these lines of code - for the mean and sum - but R keeps returning "NA" and I've searched and searched for alternatives but nothing seems to work:

Company i_ I1984 <- with(R, mean(I [FY == "1984" & Co == "AAR CORP" ]))
Company i_ REV1984 <- with(R, sum(REVQ [FY == "1984" & Co == "AAR CORP" ]))

R is my dataframe I <- quarterly inventory REVQ <- quarterly revenue

Clearly, the values in quotes will be made dynamic as I find each new average/sum value and place in a new data.frame .

Any help would be highly appreciated. Thank you

I've included an example code below:

company<-c("xray", "xray", "xray",  "xray", "foxrot", "foxrot", "delta",     "kilo", "kilo" )  
qtr <-c("1","2","3","4", "1", "2","4", "2","3")

IQ <- rnorm(9,0,10)  
REVQ <- rnorm(9,0,10)  
AssetQ <- rnorm(9,0,10)  
CashQ  <- rnorm(9,0,10)  

#Modified dataframe  
data<-data.frame( company, qtr, IQ, REVQ, AssetQ, CashQ )

In this example 'xray' should be the only company for which we take a mean/sum.

Answer 1

For your first question (with your df structure from the comments below):

company<-c("xray", "xray", "xray", "xray", "foxrot", "foxrot", "delta", "kilo", "kilo" )  
qtr <-c("1","2","3","4", "1", "2","4", "2","3")  
IQ <- rnorm(9,0,10)  
REVQ <- rnorm(9,0,10)  
AssetQ <- rnorm(9,0,10)  
CashQ <- rnorm(9,0,10)  
#Modified dataframe  
data<-data.frame(company,qtr, IQ, REVQ, AssetQ, CashQ )


#Using the dplyr package:  
data.complete<-data.frame(data %>% group_by(company) %>% filter(n() == 4))

For your second question

#Get your sum and means (note that the 'by' command will separate the sums based on the company factor when you have more than 1 company with complete data)  
aggregate(data.complete[,3:6], by=list(data.complete$company), sum)
aggregate(data.complete[,3:6], by=list(data.complete$company), mean)