如何在 R 中合并同一数据框中的行(基于特定列下的重复值)? [英] How can I combine rows within the same data frame in R (based on duplicate values under a specific column)?

问题描述

df 中 2 个(组成)示例行的示例:

Sample of 2 (made-up) example rows in df:

userid   facultyid  courseid schoolid
167       265        NA       1678  
167       71111      301      NA

假设我有几百个重复的用户 ID，就像上面的例子一样.但是，绝大多数 userid 具有不同的值.

Suppose that I have a couple hundred duplicate userid like in the above example. However, the vast majority of userid have different values.

除非第一个值为 NA(在这种情况下，NA 将重新填充任何值)从第二行开始)?

How can I combine rows with duplicate userid in such a way as to stick to the column values in the 1st (of the 2) row unless the first value is NA (in which case the NA will be repopulated with whatever value came from the second row)?

本质上，从上面的示例中得出，我的理想输出将包含:

In essence, drawing from the above example, my ideal output would contain:

userid   facultyid  courseid schoolid
167       265        301       1678  

推荐答案

aggregate(x = df1, by = list(df1$userid), FUN = function(x) na.omit(x)[1])[,-1]

或使用 dplyr 库:

library(dplyr)

df1 %>%
  group_by(userid) %>%
  summarise_each(funs(first(na.omit(.))))

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