通过根据两个定性因素组合相似的行来减少数据框答案

【问题标题】：Reduce a data frame by combining like rows according to two qualitative factors通过根据两个定性因素组合相似的行来减少数据框
【发布时间】：2021-02-12 04:38:32
【问题描述】：

我有一个如下的数据框：

observations<- data.frame(X=c("00KS089001","00KS089001","00KS089002","00KS089002","00KS089003","00KS089003","00KS105001","00KS105001", "00KS177011","00KS177011","00P0006","00P006","00P006","00P006"), hzdept = c(0,20,0,15,0,13,0,20,0,16,0,6,13,29), hzdepb = c(20,30,15,30,13,30,20,30,16,30,6,13,29,30),Y=c("Red","White","Red","White","Green","Red","Red","Blue", "Black","Black","Red","White","White","White"), Z = c(0.67,0.33,0.5,0.5,0.43,0.57,0.67,0.33,0.53,0.47,0.2,0.23,0.53,0.04))

我希望能够减少这种情况，以便任何时候 X 和 Y 对于两行相同，观察结果被合并，即

data.frame(X=c("00KS089001","00KS089001","00KS089002","00KS089002","00KS089003","00KS089003","00KS105001","00KS105001", "00KS177011","00P0006","00P006"), hzdept = c(0,20,0,15,0,13,0,20,0,0,6), hzdepb = c(20,30,15,30,13,30,20,30,30,6,30),Y=c("Red","White","Red","White","Green","Red","Red","Blue", "Black","Red","White"), Z = c(0.67,0.33,0.5,0.5,0.43,0.57,0.67,0.33,1.00,0.20,0.80))

关于如何最好地解决这个问题有什么建议吗？

【问题讨论】：

你想如何组合它们？你如何得到你的 z 值并不明显
对不起，我在 Z 栏打错了；应该更直观的看到。我想要的是把它们结合起来。 hzdept 成为同类行分组中的最小值，hzdepb 成为最大值，Z 成为组中所有 Z 的总和。

标签： r dataframe dplyr plyr

【解决方案1】：

编辑：好的，现在我从您上面的评论中看到 hzdept 和 hzdepb 应该如何组合：

library(tidyverse)

df <- observations %>% count(X,Y,wt = Z,name = "Z")

df_hzdept <- observations %>%
   arrange(hzdept) %>%
   distinct(X,Y,.keep_all = T) %>%
   select(X,Y,hzdept)

df_hzdepb <- observations %>%
   arrange(desc(hzdepb)) %>%
   distinct(X,Y,.keep_all = T) %>%
   select(X,Y,hzdepb)

df <- df %>% left_join(df_hzdept) %>% left_join(df_hzdepb)

【讨论】：

【解决方案2】：

使用 dplyr

以下是按两列分组并使用数据框中其他列的最小值、最大值和总和进行汇总的方法：

library(magrittr) # For the pipe: %>% 
observations %>%
    dplyr::group_by(X, Y) %>%
    dplyr::summarise(hzdept  = min(hzdept),
                     hzdepb  = max(hzdepb),
                     Z = sum(Z), .groups = 'drop')

【讨论】：