R-有效地查找具有几乎相同数据的行，并将差异粘贴到一个单元格中

Question

Suppose I have a data frame

 Data <- data.frame("Name", "Age", "Weight", "School", "Book" , "Author")
 Data[1,] <- c("Paul", 26, 150, "Helgason U", "Intro to Smooth Manifolds", "John Lee")
 Data[2,] <- c("Paul", 26, 150, "Helgason U", "A Tale of Two Cities", "Charles Dickens")
 Data[3,] <- c("Paul", 26, 150, "Helgason U", "Fear and Loathing in Las Vegas", "Hunter Thompson")
 Data[4,] <- c("Paul", 26, 150, "Helgason U", "Gravity's Rainbow", "Thomas Pynchon")
 Data[5,] <- c("David", 35, 165, "Turing College", "Brave New World", "Aldous Huxley")
 Data[6,] <- c("David", 35, 165, "Turing College", "Vashista's Yoga", "Vashista")
 Data[7,] <- c("David", 35, 165, "Turing College", "C++ For Dummies", "Anonymous")

and I wanted to compress the data so that all of the rows corresponding to the same person can be fit into one row, and the numerous books and authors can be concatenated. In other words, I would like my output to be:

    Name     Age     Weight     School     Books                          Authors
    Paul     26       150     Helgason U   Intro to Smooth Manifolds      John Lee
                                           A Tale of Two Cities           Charles Dickens
                                           Fear and Loathing in Las Vegas Hunter Thompson
                                           Gravity's Rainbow              Thomas Pynchon
    David    35       165   Turing College Brave New World                Aldous Huxley
                                           Vashista's Yoga                Vashista
                                           C++ For Dummies                Anonymous

Ideally I would like the books can be concatenated as "Intro to Smooth Manifolds\\nA Tale of Two Cities\\nFear and Loathing in Las Vegas\\nGravity's Rainbow" .

Originally I had used a for loop, but this was too slow since my actual data is far greater than this. To give an idea of how I was looping:

  for (i in 1:L){
    Names = subset(Data, Data$Name == unique(Data$Names)[i])
    rows = nrow(Names)

    Name_Matches = which(duplicated(Names[,Cols]) | duplicated(Names[nrow(Names):1, Cols])[nrow(Names):1])
    Name_UnMtchs = setdiff(1:nrow(Names), Name_Matches)

    Books        = Names$Book[Name_Matches]
    New_Books    = paste(as.character(Books), collapse = "\n")
    Authors     = Names$Author[Name_Matches]
    New_Authors = paste(Authors, collapse = "\n")

    New_Data[count_New, Cols] = Names[Name_Matches[1], Cols]
    New_Data$Book             = New_Books
    New_Data$Author           = New_Authors
    count_New                 = count_New + 1
    }

where Cols are the column indices of the entries which I know stay the same for a person (age, weight, school, name), L is the number of unique names in the data frame, count_New is a counter that is initialized at 1 to start, and New_Data is an empty data frame with the same columns as Data . What function could I use that would let me consolidate my data without using a for loop of this kind?

Answer 1

This kind of stuff could be done with base R, but it's probably better to use a package purposely designed for data wrangling.

In dplyr:

require(dplyr)

Data %>%
  group_by(Name, Age, Weight, School) %>%
  summarise(Books=paste(Book, collapse="\n"), Authors=paste(Author, collapse="\n"))

I suspect that this is what you really want though. Instead of pasting the book titles (and authors) into one string for each name, it turns them into a vector of titles which can then be used for further processing.

Data %>%
  group_by(Name, Age, Weight, School) %>%
  summarise(Books=list(Book), Authors=list(Author))

Answer 2

Consider this base R solution (albeit not as efficient or elegant):

# OBTAIN UNIQUE PERSONS DATAFRAME
Data2 <- unique(Data[1:4])
rownames(Data2) <- NULL

# GET LIST OF DISTINCT PERSONS
persons = c(Data2[1]) 

# LOOP THROUGH DISTINCT PERSONS
for (j in persons){
  for (k in 0:length(persons)+1){
  # BOOK COLUMN (PULL INTO LIST, THEN CONCATENATE)  
  books <- c(Data[Data$Name==j[k],][5])
  booksconcat <- paste(books[[1]], collapse="\n")
  Data2$Book[Data2$Name==j[k]] <- booksconcat    

  # AUTHOR COLUMN (PULL INTO LIST, THEN CONCATENATE)
  authors <- c(Data[Data$Name==j[k],][6])
  authorsconcat <- paste(authors[[1]], collapse="\n")
  Data2$Author[Data2$Name==j[k]] <- authorsconcat    
  }
}