动态拆分和命名数据帧

Question

I have a data frame called "loan", this contains all information like customer ID, loan amount, term of loan etc.

There is a column called "yq" which is basically the year and quarter of the loan disbursement date

    ID      yq
    1       2014 Q4
    2       2014 Q4
    3       2015 Q1
    4       2015 Q2
    5       2015 Q3  

I wanted to split the data frame based on the quarters and year, so naturally I used the following:

 list_of_dataframes <- split(loan,                  
                       with(loan, yq), 
                       drop = TRUE)

But this leads to me hard coding the split datasets like so:

      loan_2014_q4 <- list_of_dataframes[[1]]

      loan_2015_q1 <- list_of_dataframes[[2]]

Is there a way to do this better, like where the name of the dataframe is "loan" followed by the value in the row for each. Also the number of dataframes to be saved is dynamic

Basically I am trying to automate the process, thus the number of split and data frame are automatically split, named and saved.

Thanks in advance

Answer 1

Since you asked to automate, run the following after creating list_of_dataframes

temp <- unique(loan$yq)
for(i in 1:length(list_of_dataframes)) {
    assign(paste0("loan_",temp[i]),list_of_dataframes[[i]])
}

Answer 2

I would ultimately recommend you keep your data in a list (or you don't even need lists if you are using tools like "data.table" and "dplyr" which give you extremely flexible subsetting options).

However, if you really feel you need separate data.frame s, try the following:

## Assume your data.frame is called "mydf"....
temp <- split(mydf, mydf$yq, drop = TRUE)
ls()
[1] "mydf" "temp"
temp
# $`2014 Q4`
#   ID      yq
# 1  1 2014 Q4
# 2  2 2014 Q4
# 
# $`2015 Q1`
#   ID      yq
# 3  3 2015 Q1
# 
# $`2015 Q2`
#   ID      yq
# 4  4 2015 Q2
# 
# $`2015 Q3`
#   ID      yq
# 5  5 2015 Q3

Now, use list2env to put each list item into the global environment as its own object. Modify the list's names first.

list2env(setNames(temp, sprintf("loan_%s", gsub("\\s+", "_", names(temp)))), .GlobalEnv)
# <environment: R_GlobalEnv>
ls()
# [1] "loan_2014_Q4" "loan_2015_Q1" "loan_2015_Q2" "loan_2015_Q3" "mydf" "temp"
loan_2014_Q4
#   ID      yq
# 1  1 2014 Q4
# 2  2 2014 Q4