tidyr ::收集不同类型的多个列 [英] tidyr::gather multiple columns of varying types

问题描述

我的问题类似于此问题。我试图 tidyr :: gather 多个列。然而，链接中提供的解决方案不太理想，因为属性在所有列中通常不相同，因此它们被删除。

My question is similar to this question. I'm trying to tidyr::gather multiple columns. However, the solution provided in the link is less than ideal because the attributes are generally not identical across all columns and so they are dropped.

注意，我知道如何使用base R，但是我正在尝试学习如何使用tidyr和/或dplyr进行等效操作。

Note, I know how to do this with base R, but I'm trying to learn how to do the equivalent operation with tidyr and/or dplyr.

下面我已经模拟了一些数据（不好但很快），这些数据说明了我经常发现自己的情况（尽管我通常有更多的列遵循同样的模式）。我已经提供了基础解决方案，使用 stats :: reshape ，以便您可以看到我想要的输出。

Below I've simulated some data (poorly, but quickly) that illustrate the situation I often find myself in (although I generally have far more columns that follow this same sort of a pattern). I've provided the base solution with stats::reshape so you can see my desired output.

任何帮助将不胜感激。

set.seed(123)
male_g6 <- rbinom(100, 1, .5)
ell_g6 <- rbinom(100, 1, .1)
sped_g6 <- rbinom(100, 1, .15)
pullouts_g6 <- rbinom(100, 5, .1)
disability_g6 <- replicate(100, 
                sample(
                    c("asd", "cd", "ed", "hi", "id", "ohi", "ld", "none"),
                    1,
                    prob = c(rep(0.01, 6), 0.05, 0.89)
                    )
                 )
score_g6 <- rnorm(100, 200, 10)
score_g7 <- score_g6 + 5 + rnorm(100, 0, 2)
score_g8 <- score_g7 + 5 + rnorm(100, 0, 2)

d <- data.frame(
        SID = 1:100,
        male_g6 = male_g6,
        male_g7 = male_g6,
        male_g8 = male_g6,
        ell_g6 = ell_g6,
        ell_g7 = ell_g6,
        ell_g8 = ell_g6,
        sped_g6 = sped_g6,
        sped_g7 = sped_g6,
        sped_g8 = sped_g6,
        pullouts_g6 = pullouts_g6,
        pullouts_g7 = pullouts_g6,
        pullouts_g8 = pullouts_g6,
        disability_g6 = disability_g6,
        disability_g7 = disability_g6,
        disability_g8 = disability_g6,
        score_g6 = score_g6,
        score_g7 = score_g7,
        score_g8 = score_g8
    )

使用基本重塑

With base reshape

ld <- stats::reshape(d,
        idvar = "SID",
        varying = list(
            c("male_g6", "male_g7", "male_g8"),
            c("ell_g6", "ell_g7", "ell_g8"),
            c("sped_g6", "sped_g7", "sped_g8"),
            c("pullouts_g6", "pullouts_g7", "pullouts_g8"),
            c("disability_g6", "disability_g7", "disability_g8"),
            c("score_g6", "score_g7", "score_g8")
            ),
        v.names = c("male", "ell", "sped", "pullouts", "disability", "score"),
        times = 6:8,
        timevar = "Grade",
        direction = "long"
    )
ld <- ld[order(ld$SID), ]

推荐答案

你需要收集超越你想要结束的，所以你可以将成绩级别与标题分开，之后你可以回到广泛的形式：

You'll need to gather beyond what you want to end with so you can separate the grade level from the headers, after which you can spread back to wide form:

ld2 <- d %>% gather(var, val, -SID) %>%     # gather to long form
    # separate grade from variable names
    separate(var, c('var', 'grade'), sep = '_g', convert = TRUE) %>% 
    spread(var, val, convert = TRUE)    # spread back to wide

head(ld2)

##   SID grade disability ell male pullouts    score sped
## 1   1     6         cd   0    0        1 196.2440    0
## 2   1     7         cd   0    0        1 203.2739    0
## 3   1     8         cd   0    0        1 211.1347    0
## 4   2     6       none   0    1        0 194.3812    1
## 5   2     7       none   0    1        0 195.3957    1
## 6   2     8       none   0    1        0 202.4890    1

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