创建通过将函数应用于原始数据框的子集而生成的数据框的列表

Question

I'm trying to create a list of dataframes that have been created by applying a function to subsets of my original dataframe.

Here is some sample data:

Data <- data.frame("Country" = c("UK", "UK", "US", "US", "US", "France", "France", "Japan", 
"Japan", "Japan", "India", "India"), "Outcome" = c("Y", "N", "Y", "Y", "Y", "N", "N", "Y",
"N", "Y", "N", "Y"))

I'm subsetting by one of my variables (country) and applying the same function to create a new dataframe from each subset:

Data.UK <- subset(Data, Country == "UK")
UK <- as.data.frame(table(Data.UK$Outcome))
Data.US <- subset(Data, Country == "US")
US <- as.data.frame(table(Data.US$Outcome))
Data.France <- subset(Data, Country == "France")
France <- as.data.frame(table(Data.France$Outcome))
Data.Japan <- subset(Data, Country == "Japan")
Japan <- as.data.frame(table(Data.Japan$Outcome))
Data.India <- subset(Data, Country == "India")
India <- as.data.frame(table(Data.India$Outcome))

And then I'm combining these dataframes into a list:

Countries <- list(UK, US, France, Japan, India)

I'm sure there is an easier way to do this, especially for a much larger dataset with many more subsets (in my case I need to subset by every country in the world), I'm thinking I could do this by subsetting based on a character vector of the unique values for the variable I'm subsetting by, but I'm not sure how to go about this. Any help is greatly appreciated!

Answer 1

An option could be

library(dplyr)

result_by_country <- group_by(Data, Country) %>% 
  summarise(outcome_table = list(table(Outcome))) 

Then you can get the list

Countries <- result_by_country$outcome_table

Answer 2

Although it does seem like the dplyr package can be very helpful in this case, missuse gave me the idea of starting off by using the "split" function, so I ended up doing this:

List_country <- split(Data, Data$Country)
Countries_outcome <- lapply(List_country, function(x) x[2])
Countries <- lapply(Countries_outcome, function(x) as.data.frame(table(x)))

Thank you all for the input!