通过其条目过滤数据帧 [英] Filter a dataframe by its entry

问题描述

如何通过数据框中任何位置可能发生的特定值过滤数据集，但不一定在任何一列或第一行？

How do I filter a dataset by a specific value that can occur anywhere in the data frame and not necessarily under any one column or row ?

假设我有一个数据框是这样的。

Suppose I have a data frame that is like this.

   id gender group Student_Math_1 Student_Math_2 Student_Read_1 Student_Read_2
   46      M   Red             23             45             37             56
   46      M   Red             34             36             33             78
   46      M   Red             56             63             58             NA
   62      F  Blue             59             NA             NA             68
   62      F  Blue             NA             68             87             73
   38      M   Red             78             57             NA             65
   38      M   Red             NA             75             54             NA
   17      F  Blue             74             NA             56             72
   17      F  Blue             75             61             NA             79
   17      F  Blue             NA             74             43             81

我正在尝试以对数据框进行子集，使得我保留包含值 68 的所有行和列，而不管数据帧内发生的位置。

And I am trying to subset this data frame such that I retain all the rows and columns that contain the value 68 regardless of where it occurs within the data frame.

最终输出将是

   id gender group Student_Math_1 Student_Math_2 Student_Read_1 Student_Read_2

   62      F  Blue             59             NA             NA             68
   62      F  Blue             NA             68             87             73

欢迎任何提示或建议。感谢提前。

Any tips or suggestions are welcome. Thanks in advance.

df = structure(list(id = c(46, 46, 46, 62, 62, 38, 38, 17, 17, 17), 
    gender = structure(c(2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 
    1L), .Label = c("F", "M"), class = "factor"), group = structure(c(2L, 
    2L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L), .Label = c("Blue", "Red"
    ), class = "factor"), Student_Math_1 = c(23, 34, 56, 59, 
    NA, 78, NA, 74, 75, NA), Student_Math_2 = c(45, 36, 63, NA, 
    68, 57, 75, NA, 61, 74), Student_Read_1 = c(37, 33, 58, NA, 
    87, NA, 54, 56, NA, 43), Student_Read_2 = c(56, 78, NA, 68, 
    73, 65, NA, 72, 79, 81)), .Names = c("id", "gender", "group", 
"Student_Math_1", "Student_Math_2", "Student_Read_1", "Student_Read_2"
), row.names = c(NA, -10L), class = "data.frame")

推荐答案

或者，

df[unique(which(df==68, arr.ind = T)[,1]),]

#  id gender group Student_Math_1 Student_Math_2 Student_Read_1 Student_Read_2
#5 62      F  Blue             NA             68             87             73
#4 62      F  Blue             59             NA             NA             68

在这种情况下，您不需要关心列的位置，或者出现 NA 的位置。 唯一用于每一次出现68次以上的情况。

In this case, you don't need to care about the position of the columns or where NAs are appeared. unique is used in case 68 is appeared more than once per row.

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