在编程中使用dplyr filter（） [英] Using dplyr filter() in programming

问题描述

我正在编写函数，并希望使用dplyr的filter（）函数来选择数据框中满足条件的行。这是我的代码：

I am writing my function and want to use dplyr's filter() function to select rows of my data frame that satisfy a condition. This is my code:

library(tidyverse)

df <-data.frame(x = sample(1:100, 50), y = rnorm(50), z = sample(1:100,50), w = sample(1:100, 50),
            p = sample(1:100,50))

new <- function(ang,brad,drau){
  df%>%filter(!!drau %in% 1:50)%>%select(ang,brad) -> A
return(A)
}

brand <- c("z","w","p")
lapply(1:3, function(i) new(ang = "x", brad = "y", drau = brand[i]))%>%bind_rows()

每次运行此功能时，过滤器看起来都不会选择满足条件的任何行。

Anytime I run this function, it looks like filter doesn't select any rows that satisfy the condition.

如何进行这项工作？

更新

出于某些原因，当我不使用时，此方法有效`％in％，如；

For some reason, this works when I don't use `%in%, as in;

new <- function(ang,brad,drau){
  df%>%filter(!!drau > 50)%>%select(ang,brad) -> A
return(A)
}

lapply(1:3, function(i) new(ang = "x", brad = "y", drau = brand[i]))%>%bind_rows()

但是，每个循环的结果都相同。为什么会这样呢？以及为什么我不能使用％in％。

However, the results are the same for every loop. Why is this so? and also why can't I use %in%.

推荐答案

这似乎可以满足您的要求（但需要您的确认）：

This appears to do what you want (but it needs confirmation by you):

library(tidyverse)
library(rlang)

set.seed(1492)

xdf <- data_frame(
  x = sample(1:100, 50),
  y = rnorm(50), 
  z = sample(1:100,50), 
  w = sample(1:100, 50),
  p = sample(1:100,50)
)

new_df <- function(ang, brad, drau) {
  drau <- sym(drau)
  filter(xdf, UQE(drau) %in% 1:50) %>% 
    select(ang, brad)
}

brand <- c("z", "w", "p")

map_df(brand, ~new_df(ang = "x", brad = "y", drau = .x))

尽管有很多使用<$的官方 tidyverse示例c $ c> df ，这是 stats pkg中的函数，我尝试避免再使用它。

Despite there being a plethora of "official" "tidyverse" examples using df, it's a function in the stats pkg and I try to avoid using it anymore.

由于您使用的是tidyverse，因此不妨利用<$ c $中的 map_df（） c> purrr 。

Since you're using the tidyverse, might as well take advantage of map_df() from purrr.

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