删除所有列中具有相同值的行 [英] Remove rows with the same value across all columns

问题描述

假设我有一个数据帧(df)，如下所示:

Suppose I have a data frame (df) that looks like below:

options(stringsAsFactors = F)

cars <- c("Car1", "Car2", "Car3", "Car4", "Car5", "Car6", "Car7", "Car8", "Car9")
test1 <- c(0,0,3,1,4,2,1,3,0)
test2 <- c(0,0,2,1,0,2,2,5,0)
test3 <- c(1,0,5,1,2,2,6,7,0)
test4 <- c(2,NA,2,1,2,2,1,1,0)
test5 <- c(0,0,1,1,0,2,1,3,0)
test6 <- c(1,0,1,1,1,2,3,4,0)
test7 <- c(3,0,2,1,0,2,1,1,0)

df <- data.frame(cars,test1,test2,test3,test4,test5,test6,test7)

#df
   cars test1 test2 test3 test4 test5 test6 test7
#1 Car1     0     0     1     2     0     1     3
#2 Car2     0     0     0    NA     0     0     0
#3 Car3     3     2     5     2     1     1     2
#4 Car4     1     1     1     1     1     1     1
#5 Car5     4     0     2     2     0     1     0
#6 Car6     2     2     2     2     2     2     2
#7 Car7     1     2     6     1     1     3     1
#8 Car8     3     5     7     1     3     4     1
#9 Car9     0     0     0     0     0     0     0

我要删除整行中具有相同值的所有行(在上面的示例中，我想保留第1、3、5、7、8行并删除其余行).

I want to remove any rows that have the same value throughout the entire row (in the example above, I would like to keep rows 1, 3, 5, 7, 8 and remove the rest).

我已经找到了如何删除所有具有零的行

I've figured out how to remove all rows that have zeros

 df$sum <- rowSums(df[,c(2:8)], na.rm = T )
 df.all0 <- df[which(df$sum == 0),]

但是，这不一定适用于所有其他行.与其他问题不同，该问题要求在整个行中查找重复项，而不仅仅是特定的列.

However, this doesn't necessarily work for all the other rows. Unlike other questions, this question asks to look for duplicates across the entire row, not just specific columns.

任何帮助将不胜感激！

推荐答案

keep <- apply(df[2:8], 1, function(x) length(unique(x[!is.na(x)])) != 1)
df[keep, ]

  cars test1 test2 test3 test4 test5 test6 test7
1 Car1     0     0     1     2     0     1     3
3 Car3     3     2     5     2     1     1     2
5 Car5     4     0     2     2     0     1     0
7 Car7     1     2     6     1     1     3     1
8 Car8     3     5     7     1     3     4     1

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