根据上一列中的值按比例填充新变量？

debugcn 发表于 Dev

盖伊

我想使用数据框中其他地方的信息创建一个新变量。这看起来很简单，但我想按比例分配新变量的级别。

我有一个数据框：

dd<-read.table(text="
group     piece      answer
group1     A          noise
group1     A          silence
group1     A          silence
group1     B          silence
group1     B          loud_noise
group1     B          noise
group1     B          loud_noise
group1     B          noise
group2     C          silence
group2     C          silence", header=TRUE)

我想创建一个具有两个级别的新变量“majority_annotation”：好和坏。好意味着每件作品都有多数答案同意（> 55％）。坏意味着该片没有多数答案同意。

    group     piece      answer       majority_agreement
    group1     A          noise       good 
    group1     A          silence     good
    group1     A          silence     good
    group1     B          silence     bad
    group1     B          loud_noise  bad
    group1     B          noise       bad
    group1     B          loud_noise  bad
    group1     B          noise       bad
    group2     C          silence     good
    group2     C          silence     good

我可以以二进制方式执行此操作（全部或不同意）：

    newdf <- df %>% 
      group_by(group) %>% 
      mutate(majority_agreement = ifelse(length(unique(answer)) <= 1,        
    'good', 
          ifelse(length(unique(answer) > 1) & 
          (length(unique(answer)) >= 2), 'bad', 'bad'))) %>% 
      as.data.frame

我怎么能按比例做呢？

乔恩·斯普林

library(dplyr)
newdf <- df %>% 
  count(group, piece, answer) %>%   # How many of each answer for each group & piece
  group_by(group, piece) %>%
  mutate(share = n / sum(n)) %>%  # What share have this answer?
  summarize(max_share = max(share)) %>%  # What's the largest share among them?
  mutate(majority_agreement = if_else(max_share > 0.55, "good", "bad")) %>%
  ungroup() %>%
  right_join(df)  # Add the conclusion back to the original data

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