【问题标题】:recode multiple values in shared column across many dataframes with a grouping variable使用分组变量重新编码跨多个数据帧的共享列中的多个值
【发布时间】:2019-01-26 22:16:53
【问题描述】:

编辑:我稍微改变了原始问题的代表,因为它没有产生与我实际使用类似的示例。

这是对上一个问题recode/replace multiple values in a shared data column to a single value across data frames 的扩展,它非常适合更简单的应用程序。我尝试将解决方案扩展到稍微复杂的情况,但无济于事。 我有许多不同的数据框,所有这些数据框都有一些共享列(下面的 repex 中的“site”和“grp”)。在每个数据帧中,在“grp”变量中存在多个错误,一些共享一些错误。在上一个问题中,这是使用 tidyverserecode 函数解决的,方法是创建一个键/值元素的 list 并使用

keyval <- setNames(rep(good_values, lengths(bad_values)), unlist(bad_values))
out <- map(df_list, ~ .x %>% 
                  mutate(grp = recode_factor(grp, !!! keyval)))

但是,当键/值列表依赖于另一个共享变量“站点”的值时,我想这样做。例如,当站点 = s1 时 grp = a1 应重新编码为 grp = a,当站点 = s2 时应重新编码为 grp = f。我已经尝试使用map() 扩展上述代码,并在下面的示例中嵌套调用pmap()

#example data frames
library(tidyverse)
df1 = data.frame(site = c(rep("s1",5), rep("s2",5), rep("s3",5)),grp = c("a1","a.","a.",rep("b",4),"b2","b-","bq",rep("a1",5)), measure = rnorm(15))

df2 = data.frame(site = c(rep("s1",10), rep("s2",16), rep("s3",5)), grp = c(rep("as", 3), "b2",rep("a",22),rep("a1",5)), measure2 = rnorm(31))

df3 = data.frame(site = c(rep("s1",3), rep("s2",6), rep("s3",5)),grp = c(rep("b-",3),rep("bq",2),"a", rep("a.", 3),rep("a1",5)), measure3 = 1:14)

df_list = list(df1, df2, df3)

site_list = c("s1","s2","s3")
bad_values = list(c("a1","a.","as", "b2", "b-", "bq"),
                  c("a1","a.","as","b", "b2", "b-", "bq"),
                  c("a1"))
good_values = list(c("a", "a1","a2","b","b1","b2"),
                   c("f","f1","f2","g","g","g1","g2"),
                   c("t"))
#put dfs into list to `map` over
df_list = list(df1, df2, df3)

#what I tried.
#nested pmap() within map()
dfs_mod = map(df_list, ~.x %>%
              pmap(list(site_list,bad_values,good_values),
                   ~mutate(.x, grp = ifelse(site == ..1,recode(grp, !!!setNames(as.list(..2),..3)),grp))))

目前这会引发错误代码“错误:不知道如何从一种语言中提取”。搜索此错误,我无法理解错误是什么或如何完成任务。

编辑:我试过了也试过了

keyval = map2(good_values, bad_values, ~setNames(as.list(..1),unlist(..2)))
#this creates 3 lists of key/val elements to recode grp on for each site

dfs_mod = map(df_list, function(x){
  map2(site_list, keyval, ~mutate(x, grp = ifelse(site == ..1, recode_factor(grp, !!!..2), grp)))
})

这不会引发错误,但也不能完全实现我想要的。它有几个不受欢迎的副作用:1)它创建了 3 个包含 3 个数据帧的列表,为每个 key/val 列表重新编码了一个 df 和 2)它将因子“grp”重新编码为一个整数(这让我感到困惑)。越来越清楚的是,我误解了 map*() 的用途,并且不喜欢使用它。因此,任何其他迭代地完成此任务的方法都将受到欢迎。

我想预期的输出可能是list,长度与 df_list 相同(在本例中为 3)。 'grp' variables = 'bad_values' 应重新编码为 'good_values',具体取决于列表元素位置和“站点”(例如 bad_values[[1]][1] -> good_values[[1]][1 ]、bad_values[[1]][2] -> good_values[[1]][2] 等,用于 site = site_list[[1]])。 'dfs_mod' list 中的第一个数据框应该是这样的:

dfs_mod[[1]]

   site grp    measure
1    s1  a -1.2169476
2    s1  a1  1.0644877
3    s1  a1  0.2007733
4    s1   b  0.8613291
5    s1   b -0.3682463
6    s2   g  1.2535321
7    s2   g  0.7622614
8    s2   g  1.4022664
9    s2   g1 -0.8234464
10   s2   g2 -1.0000354 
11   s3   t  1.34320583
12   s3   t  1.33950010
13   s3   t -1.12670074
14   s3   t  1.59890652
15   s3   t  0.23932814

感谢您的帮助。

#old repex data from original question that has been edited above
library(tidyverse)
#create example dfs
df1 = data.frame(site = c(rep("s1",5), rep("s2",5)),grp = c("a1","a.","a.",rep("b",4),"b2","b-","bq"), measure = rnorm(10))

df2 = data.frame(site = c(rep("s1",10), rep("s2",16)), grp = c(rep("as", 3), "b2",rep("a",22)), measure2 = rnorm(26))

df3 = data.frame(site = c(rep("s1",3), rep("s2",6)),grp = c(rep("b-",3),rep("bq",2),"a", rep("a.", 3)), measure3 = 1:9)

site_list = list("s1","s2")
bad_values = list(c("a1","a.","as", "b2", "b-", "bq"),
                   c("a1","a.","as","b", "b2", "b-", "bq"))
good_values = list(c("a", "a1","a2","b","b1","b2"),
                   c("f","f1","f2","g","g","g1","g2"))

【问题讨论】:

    标签: r tidyverse purrr


    【解决方案1】:

    我找到了一种完成这项任务的方法,该方法可以通过几个 for 循环并使用对上一个(链接的)问题的答案来快速运行。如此简单,尴尬,我花了这么长时间。

    library(tidyverse)
    keys = map2(good_values, bad_values, ~setNames(as.list(..1),unlist(..2)))
    
    # how to accomplish
    for(i in 1:length(site_list)){
      for(df in 1:length(df_list)){
        df_list[[df]] <- pluck(df_list, df) %>%
          mutate(grp = if_else(site == pluck(site_list,i), recode(grp, !!!pluck(keys,i)),grp))
      }
    }
    
    df_list[[1]]
       site grp     measure
    1    s1   a  0.60083152
    2    s1  a1 -0.56181835
    3    s1  a1  1.31789556
    4    s1   b -2.06659322
    5    s1   b  1.21575623
    6    s2   g -1.05263188
    7    s2   g  1.68731655
    8    s2   g -0.59827489
    9    s2  g1 -2.22322604
    10   s2  g2  0.22577945
    11   s3   t -0.08614122
    12   s3   t  0.74511934
    13   s3   t  1.29782596
    14   s3   t -1.87684060
    15   s3   t -0.90672568
    

    【讨论】:

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