过滤N列以获取特定值

时间:2019-01-27 20:09:53

标签: r dplyr

我有一个大型数据框,其中包含超过100个条件的布尔列(这不是理想的设置,但是我无法更改)。我正在尝试制作一个函数,该函数接受可变数量的条件列,然后过滤所有条件为1或全部为零的过滤器。

设置

library(dplyr)
set.seed(123)
ID <- sample(1:5, 20, replace = TRUE)
Val <- round(runif(length(ID), 20, 40),0)
cond_1 <- sample(0:1, length(ID), replace = TRUE)
cond_2 <- sample(0:1, length(ID), replace = TRUE)
cond_3 <- sample(0:1, length(ID), replace = TRUE)
cond_4 <- sample(0:1, length(ID), replace = TRUE)


df <- data.frame(ID, Val, cond_1, cond_2, cond_3, cond_4, stringsAsFactors = FALSE)

任意两列所需功能的示例:

filterTwoCols <- function(df, cols){

  # Select desired conditions
  df1 <- df %>% 
    select(ID, Val, one_of(cols))

  #### Filter on all conditions == 0 or all conditions == 1
  df2 <- df1 %>% 
    filter(.[,ncol(.)] == 1 & .[,ncol(.) - 1] == 1 |
           .[,ncol(.)] == 0 & .[,ncol(.) - 1] == 0)

  return(df2)
}

filterTwoCols(df, c('cond_1', 'cond_4'))
filterTwoCols(df, c('cond_3', 'cond_2'))

我想做的是命名任意数量的条件(例如filterManyCols(df, c('cond_1', 'cond_3', 'cond_4')),但是我不知道如何在不明确地在过滤器中命名它们的情况下.[,ncol(.) - 2] == 1.[,ncol(.) - 3] == 1等)。如果所选的列数与过滤器中的条件数不匹配,那么它将不起作用。有什么想法吗?

1 个答案:

答案 0 :(得分:2)

一个选项是filter_at

library(tidyverse)
filterManyCols <- function(df, cols){

 # Select desired conditions
 # Not clear whether we need to subset the columns or get the filtered 
 # full dataset columns
 # df <- df %>% 
 #       select(ID, Val, one_of(cols))

  map_df(0:1, ~ df %>%
                  filter_at(vars(one_of(cols)), all_vars(. == .x)))
 }

filterManyCols(df, c('cond_1', 'cond_4')) 
filterManyCols(df, c('cond_1', 'cond_2', 'cond_3'))   
filterManyCols(df, c('cond_1', 'cond_2', 'cond_3', 'cond_4'))