使用dplyr :: Select s select select s base r grepl和匿名函数

发布于 2025-01-28 16:03:57 字数 1021 浏览 3 评论 0原文

这里有一个非常相似的问题：如何基于基于基于列的列dplyr :: tibble grep

但是，我认为select_if用select（white（））超过。

我知道我可以执行以下操作，并且可以使用：

# select all columns with three characters
mtcars %>% 
  select(
    matches("^[a-zA-Z]{3}$")
  )

但是我也可以使用匿名函数（在此处所有列值而不是名称上）选择列。

mtcars %>% 
  select(
    where(function(x)sum(is.na(x)) == 0)
  )

因此，我认为我可以使用Anonymus函数和grepl来选择列。而且这不起作用：

mtcars %>% 
  select(
    where(
      function(x) grepl("^[a-zA-Z]{3}$", x)
    )
  )

我该如何完成这项工作？我的意思是我总是可以使用匹配助手。但是我只想了解如何使用

select（where（））语句在dataframe的名称上使用，而不是列中的所有值。

更新

这起作用：

mtcars %>% 
  select(
      which(grepl("^[a-zA-Z]{3}$", names(.)))
  )

但是我不确定是否没有更好的方法;）

原文

There is a very similar question here: How to select columns based on grep in dplyr::tibble

However I think that the select_if was superseeded with select(where()).

I know that I can do the following and it works:

# select all columns with three characters
mtcars %>% 
  select(
    matches("^[a-zA-Z]{3}quot;)
  )

But I can also use an anonymus function (here over all the column values and not the names) to select columns.

mtcars %>% 
  select(
    where(function(x)sum(is.na(x)) == 0)
  )

So I thought I could use an anonymus function and grepl to select columns. And this does not work:

mtcars %>% 
  select(
    where(
      function(x) grepl("^[a-zA-Z]{3}quot;, x)
    )
  )

How could I make this work? I mean I could always use the matches helper. But I would just like to understand how to use

select(where()) statement over the names of the dataframe and not over all the values in a column.

Update

This works:

mtcars %>% 
  select(
      which(grepl("^[a-zA-Z]{3}quot;, names(.)))
  )

But I am not sure if there isn't a better way;)

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作妖 2025-02-04 16:03:57

您可以只使用grep（）与select> select（），而没有whene（）函数。

mtcars %>% 
  select(grep("^[a-zA-Z]{3}$", names(.)))

您的初始尝试无效，因为在此代码中：

mtcars %>% 
  select(
    where(
      function(x) grepl("^[a-zA-Z]{3}$", x)
    )
  )

x在中，其中（）函数是变量的值，而不是变量的名称。这就是为什么如果您做过之类的操作（is.numeric）有效的原因 - 因为它可以代替实际值。

You could just use grep() with select() without the where() function.

mtcars %>% 
  select(grep("^[a-zA-Z]{3}quot;, names(.)))

Your initial attempt didn't work because in this code:

mtcars %>% 
  select(
    where(
      function(x) grepl("^[a-zA-Z]{3}quot;, x)
    )
  )

the x in the where() function are the values of the variable and not the name of the variable. That's why it works if you did something like where(is.numeric) works - because it is substituting the actual values.

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久隐师 2025-02-04 16:03:57

base r选项：

mtcars[grepl("^[a-zA-Z]{3}$", names(mtcars))]

输出：

                     mpg cyl
Mazda RX4           21.0   6
Mazda RX4 Wag       21.0   6
Datsun 710          22.8   4
Hornet 4 Drive      21.4   6
Hornet Sportabout   18.7   8
Valiant             18.1   6
Duster 360          14.3   8
Merc 240D           24.4   4
Merc 230            22.8   4
Merc 280            19.2   6
Merc 280C           17.8   6
Merc 450SE          16.4   8
Merc 450SL          17.3   8
Merc 450SLC         15.2   8
Cadillac Fleetwood  10.4   8
Lincoln Continental 10.4   8
Chrysler Imperial   14.7   8
Fiat 128            32.4   4
Honda Civic         30.4   4
Toyota Corolla      33.9   4
Toyota Corona       21.5   4
Dodge Challenger    15.5   8
AMC Javelin         15.2   8
Camaro Z28          13.3   8
Pontiac Firebird    19.2   8
Fiat X1-9           27.3   4
Porsche 914-2       26.0   4
Lotus Europa        30.4   4
Ford Pantera L      15.8   8
Ferrari Dino        19.7   6
Maserati Bora       15.0   8
Volvo 142E          21.4   4

Base R option:

mtcars[grepl("^[a-zA-Z]{3}quot;, names(mtcars))]

Output:

                     mpg cyl
Mazda RX4           21.0   6
Mazda RX4 Wag       21.0   6
Datsun 710          22.8   4
Hornet 4 Drive      21.4   6
Hornet Sportabout   18.7   8
Valiant             18.1   6
Duster 360          14.3   8
Merc 240D           24.4   4
Merc 230            22.8   4
Merc 280            19.2   6
Merc 280C           17.8   6
Merc 450SE          16.4   8
Merc 450SL          17.3   8
Merc 450SLC         15.2   8
Cadillac Fleetwood  10.4   8
Lincoln Continental 10.4   8
Chrysler Imperial   14.7   8
Fiat 128            32.4   4
Honda Civic         30.4   4
Toyota Corolla      33.9   4
Toyota Corona       21.5   4
Dodge Challenger    15.5   8
AMC Javelin         15.2   8
Camaro Z28          13.3   8
Pontiac Firebird    19.2   8
Fiat X1-9           27.3   4
Porsche 914-2       26.0   4
Lotus Europa        30.4   4
Ford Pantera L      15.8   8
Ferrari Dino        19.7   6
Maserati Bora       15.0   8
Volvo 142E          21.4   4

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