按两个变量分组汇总 [英] Summarizing by group of two variables

问题描述

考虑一个简化的数据集（实际数据集具有更多的行和列）：

Consider a simplified dataset (the real one has more columns and rows):

df
    tp tf   weight
1  FWD RF 78.86166
2   MF LF 81.04566
3  DEF LF 80.70527
4  DEF LF 82.96071
5  DEF RF 78.42544
6   GK LF 79.37686
7  DEF RF 78.79928
8   MF RF       NA
9   MF RF 78.93815
10 DEF RF 80.00284

我想通过分组的tp和tf的中位数来填充重量的缺失值

I want to fill the missing values in weight by the grouped median of tp and tf combined

什么我直到现在都尝试过以下操作（我使用过dlpyr）

What i have tried till now is the following (I have used dlpyr)

temp <- df %>% group_by(tp,tf) %>% summarise(mvalue = median(weight,na. rm = TRUE))

这使temp为：

temp
Source: local data frame [6 x 3]
Groups: tp [?]

      tp     tf   mvalue
  <fctr> <fctr>    <dbl>
1    DEF     LF 81.83299
2    DEF     RF 78.79928
3    FWD     RF 78.86166
4     GK     LF 79.37686
5     MF     LF 81.04566
6     MF     RF 78.93815

现在，我无法弄清楚如何用相应的组中位数来填充df中的缺失值。

Now i am unable to figure out how to fill the missing values in df with the corresponding group median.

在我的简单情况下，只有一个NA对应于tp = MF和tf = RF，如果您看一下温度，
的中位数为78.93815

In my simple case there is only one NA corresponding to tp = MF and tf = RF, the median value if you look up at temp is 78.93815

一般而言，我该怎么做？不要建议您是否有比我最初的方法更好的方法。

How do i do this in general? Do suggest if you have a better approach than my initial one.

编辑：
如果

推荐答案

您可以尝试，

library(dplyr)
df %>% 
   group_by(tp, tf) %>% 
   mutate(weight = replace(weight, is.na(weight), median(weight, na.rm = TRUE)))

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