Re: [問題] 如何將一個欄位按降冪排列變成另一個欄位

看板R_Language作者ddtwu (<囧>真夭壽)時間8年前 (2017/08/13 21:24)推噓0(0推 0噓 0→)

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※ 引述《celestialgod (天)》之銘言： : ※ 引述《henry48124 (= =)》之銘言： : : [問題類型]: : : 程式諮詢(我想用R 做某件事情，但是我不知道要怎麼用R 寫出來) : : [軟體熟悉度]: : : 入門(寫過其他程式，只是對語法不熟悉) : : [問題敘述]: : : 各位大大好，我有一筆資料長得像是： : : head(df) : : id place count : : 1 A 1 : : 1 B 1 : : 2 B 1 : : 2 C 3 : : 3 D 2 : : 4 A 1 : : 4 C 2 : : 4 D 5 : : 5 B 1 : : 我希望能讓他變成 : : id count top_place1 top_place2 : : 1 2 A B : : 2 4 C B : : 3 2 D : : 4 8 D C : : 5 1 B : : [程式範例]: : : 這是我目前的做法，總覺得寫得怪怪的，如果未來要做到 top100 就不能這樣寫 : : 謝謝各位 Orz : : library(dplyr) : : answer <- NULL : : for(x in as.list(unique(df$id))) { : : df_id <- df %>% : : filter(id == x) %>% : : arrange(-count) : : count <- sum(df$count) : : top_place1 <- NA : : top_place2 <- NA : : col <- c(x, count, top_place1, top_place2) : : for(y in 1:nrow(df_id)) { : : if(y <= 2) { : : col[y+2] <- df_id[y,]$place : : } : : answer <- rbind(answer, col) : : } : : [環境敘述]: : : [關鍵字]: : method 1是硬幹，可以直接先看method 2 : library(data.table) : library(stringr) : library(pipeR) : DT <- data.table(id = rep(1:5, c(2,2,1,3,1)), : place = c("A","B","B","C","D","A","C","D","B"), : count = c(1,1,1,3:1,2,5,1)) : ## method 1: : setorder(DT, id, -count, -place) : numRank <- 3 : DT[ , .(lapply(1:numRank, function(i){ : ifelse(length(place) >= i, place[i], "") : }) %>>% transpose %>>% sapply(str_c, collapse = ",")), by = .(id)] %>>% : `[`(j = str_c("top_place", 1:numRank) := transpose(str_split(V1, ",")), : by = .(id)) %>>% : `[`(j = V1 := NULL) %>>% : merge(DT[ , .(count = sum(count)), by = .(id)], by = "id") : # id top_place1 top_place2 top_place3 count : # 1: 1 A B 2 : # 2: 2 C B 4 : # 3: 3 D 2 : # 4: 4 D C A 8 : # 5: 5 B 1 : ## method 2: : setorder(DT, id, -count, -place) : numRank <- 3 : DT[ , rr := length(count) - frank(count, ties.method = "first")+1, by = .(id)] : DT[rr %in% 1:numRank] %>>% : dcast(id ~ rr, value.var = "place") %>>% : setnames(as.character(1:numRank), str_c("top_place", 1:numRank)) %>>% : merge(DT[ , .(count = sum(count)), by = .(id)], by = "id") : # id top_place1 top_place2 top_place3 count : # 1: 1 A B NA 2 : # 2: 2 C B NA 4 : # 3: 3 D NA NA 2 : # 4: 4 D C A 8 : # 5: 5 B NA NA 1 我的作法是這樣： library(dplyr) library(magrittr) library(tidyr) df <- data.frame(id = rep(1:5, c(2,2,1,3,1)), place = c("A","B","B","C","D","A","C","D","B"), count = c(1,1,1,3:1,2,5,1), stringsAsFactors = FALSE) %>% tbl_df() df %>% group_by(id) %>% mutate(seq = order(count, decreasing = TRUE), sumCount = sum(count)) %>% filter(seq <= 2) %>% ungroup() %>% mutate(seqName = sprintf('top_place%s', seq)) %>% select(-count, -seq) %>% spread(key = seqName, value = place, fill = NA) # A tibble: 5 x 4 id sumCount top_place1 top_place2 * <int> <dbl> <chr> <chr> 1 1 2 A B 2 2 4 C B 3 3 2 D <NA> 4 4 8 D C 5 5 1 B <NA> -- ※ 發信站: 批踢踢實業坊(ptt.cc), 來自: 1.160.116.220 ※ 文章網址: https://www.ptt.cc/bbs/R_Language/M.1502630653.A.3AD.html