如何將寬范圍的連續數據重整為長類別的數據？

Question

我的數據采用以下寬格式，根據SUBJECT_ID按行顯示，總共觀察到變量X和Y ，然后觀察到元數據的各個列，例如SUBJECT_BIRTHYEAR ， SUBJECT_HOMETOWN ：

variableX    variableY    SUBJECT_ID     SUBJECT_BIRTHYEAR     SUBJECT_HOMETOWN
2            1            A              1950                  Townsville
1            2            B              1951                  Villestown

我想將它們轉換為以下長格式，其中對於每個SUBJECT_ID變量X和Y每次觀察：

VARIABLE     SUBJECT_ID     SUBJECT_BIRTHYEAR     SUBJECT_HOMETOWN
X            A              1950                  Townsville
X            A              1950                  Townsville
Y            A              1950                  Townsville
X            B              1951                  Villestown
Y            B              1951                  Villestown
Y            B              1951                  Villestown

我的問題的具體內容是如何將n個連續變量的觀測值轉換為n行分類數據。

Answer 1

嘗試以下

數據

df <- read.table(text="variableX    variableY    SUBJECT_ID     SUBJECT_BIRTHYEAR     SUBJECT_HOMETOWN
2            1            A              1950                  Townsville
1            2            B              1951                  Villestown", header=TRUE)

解

library(tidyverse)
result <- df %>%
        nest(variableX, variableY, .key="VARIABLE") %>%
        mutate(VARIABLE = map(VARIABLE, function(i) {
                                    vec <- unlist(i)
                                    rep(gsub("variable", "", names(vec)), times=vec)
                                })) %>%
        unnest()

# A tibble: 6 x 4
  # SUBJECT_ID SUBJECT_BIRTHYEAR SUBJECT_HOMETOWN VARIABLE
      # <fctr>             <int>           <fctr>    <chr>
# 1          A              1950       Townsville        X
# 2          A              1950       Townsville        X
# 3          A              1950       Townsville        Y
# 4          B              1951       Villestown        X
# 5          B              1951       Villestown        Y
# 6          B              1951       Villestown        Y

Answer 2

該問題要求dcast()的調用反轉，該調用已使用length()作為聚合函數將數據從長格式整形為寬格式。

這可以通過調用melt()以及一些其他轉換來實現：

library(data.table)
# reshape wide back to long format
long <- melt(setDT(wide), measure.vars = c("variableX", "variableY"))[
  # undo munging of variable names
  , variable := stringr::str_replace(variable, "^variable", "")][]
# undo effect of aggregation by length()
result <- long[long[, rep(.I, value)]][
  # beautify result
  order(SUBJECT_ID), !"value"]
result

  SUBJECT_ID SUBJECT_BIRTHYEAR SUBJECT_HOMETOWN variable 1: A 1950 Townsville X 2: A 1950 Townsville X 3: A 1950 Townsville Y 4: B 1951 Villestown X 5: B 1951 Villestown Y 6: B 1951 Villestown Y 

.I是保存行位置（即行索引）的特殊符號。

---

為了證明這確實是逆運算，可以重新調整result wide以重現：

dcast(result, ... ~ paste0("variable", variable), length, value.var = "variable")

  SUBJECT_ID SUBJECT_BIRTHYEAR SUBJECT_HOMETOWN variableX variableY 1: A 1950 Townsville 2 1 2: B 1951 Villestown 1 2 

數據

library(data.table)
wide <- fread("variableX    variableY    SUBJECT_ID     SUBJECT_BIRTHYEAR     SUBJECT_HOMETOWN
2            1            A              1950                  Townsville
1            2            B              1951                  Villestown")

Answer 3

這是使用base R的選項

res <- cbind(VARIABLE = rep(substr(names(df1)[1:2], 9, 9)[row(df1[1:2])], t(df1[1:2])), 
        df1[rep(seq_len(nrow(df1)), rowSums(df1[1:2])), -(1:2)])
row.names(res) <- NULL
res
#   VARIABLE SUBJECT_ID SUBJECT_BIRTHYEAR SUBJECT_HOMETOWN
#1        X          A              1950       Townsville
#2        X          A              1950       Townsville
#3        Y          A              1950       Townsville
#4        X          B              1951       Villestown
#5        Y          B              1951       Villestown
#6        Y          B              1951       Villestown