根据它们的属性选择列如何操作？

huangapple
go评论101阅读模式
英文:

How to select columns based on their properties?

问题

以下是根据您提供的信息生成的筛选数据框的代码示例：

在基本R中：

  1. # 创建示例数据框
  2. df <- data.frame(
  3.   c1 = rep(0, 7),
  4.   c2 = rep(1, 7),
  5.   c3 = rep(0, 7),
  6.   c4 = rep(1, 7),
  7.   c5 = c("?", 1, 1, 1, 1, 1, 1),
  8.   c6 = c("?", 0, 0, 0, 0, 0, 0),
  9.   c7 = c("?", "?", 0, 0, 0, 0, 0),
  10.   c8 = c("?", "?", 1, 1, 1, 1, 1),
  11.   c9 = rep(0, 7),
  12.   c10 = rep(1, 7)
  13. )
  15. # 移除所有列中的 0 或 1
  16. df_filtered <- df[, !sapply(df, function(x) all(x %in% c(0, 1)))]
  18. # 移除包含 "?" 的列
  19. df_filtered <- df_filtered[, !sapply(df_filtered, function(x) any(x == "?"))]

在Tidyverse中：

  1. library(dplyr)
  3. # 创建示例数据框
  4. df <- data.frame(
  5.   c1 = rep(0, 7),
  6.   c2 = rep(1, 7),
  7.   c3 = rep(0, 7),
  8.   c4 = rep(1, 7),
  9.   c5 = c("?", 1, 1, 1, 1, 1, 1),
  10.   c6 = c("?", 0, 0, 0, 0, 0, 0),
  11.   c7 = c("?", "?", 0, 0, 0, 0, 0),
  12.   c8 = c("?", "?", 1, 1, 1, 1, 1),
  13.   c9 = rep(0, 7),
  14.   c10 = rep(1, 7)
  15. )
  17. # 移除所有列中的 0 或 1
  18. df_filtered <- df %>%
  19.   select_if(~!all(. %in% c(0, 1)))
  21. # 移除包含 "?" 的列
  22. df_filtered <- df_filtered %>%
  23.   select_if(~!any(. == "?"))

无论您选择使用基本R还是Tidyverse，上述代码将生成一个新的数据框df_filtered，其中不包含所有列都是0或1的列以及包含"?"的列。

英文:

I have a data frame with the following three values: 0, 1, and ?. The 0s and 1s are characters and not numeric data. I am trying to subset the data frame to remove the following:

  1. All columns that are uniformly 0 or 1
  2. All columns that have at least one ?

So the dataset should no invariant columns or columns with missing values.

Here is an illustration of the data frame:

  1.    c1 c2 c3 c4 c5 c6 c7 c8 c9 c10
  2. r1 0  1  0  1  ?  ?  ?  ?  0  1
  3. r2 0  1  0  1  1  0  ?  ?  0  1
  4. r3 0  1  0  1  1  0  0  1  1  0
  5. r4 0  1  0  1  1  0  0  1  1  0
  6. r5 0  1  0  1  1  0  0  1  ?  1
  7. r6 0  1  0  1  1  0  0  1  ?  0
  8. r7 0  1  1  0  1  0  0  1  0  0

So I want to exclude c1, c2, c5, c6, c7, c8, and c9. How do I do this in base R or tidyverse?

答案1

得分: 3

在tidyverse中：

  1. df %>% select_if(~!any(.x == '?') & !all(.x == 1) & !all(.x == 0))
  2.    c3 c4 c10
  3. r1  0  1   1
  4. r2  0  1   1
  5. r3  0  1   0
  6. r4  0  1   0
  7. r5  0  1   1
  8. r6  0  1   0
  9. r7  1  0   0
英文:

In tidyverse:

  1. df %&gt;% select_if(~!any(.x == &#39;?&#39;) &amp; !all(.x == 1) &amp; !all(.x == 0))
  2.    c3 c4 c10
  3. r1  0  1   1
  4. r2  0  1   1
  5. r3  0  1   0
  6. r4  0  1   0
  7. r5  0  1   1
  8. r6  0  1   0
  9. r7  1  0   0

答案2

得分: 2

  1.     &gt; sapply(df, is.integer) &amp; colMeans(df == 0) &lt; 1 &amp; colMeans(df == 1) &lt; 1
  2.        c1    c2    c3    c4    c5    c6    c7    c8    c9   c10 
  3.     FALSE FALSE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE  TRUE
英文: 
  1. &gt; sapply(df,is.integer) &amp; colMeans(df==0)&lt;1 &amp; colMeans(df==1)&lt;1
  2.    c1    c2    c3    c4    c5    c6    c7    c8    c9   c10 
  3. FALSE FALSE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE  TRUE

huangapple
  • 本文由 发表于 2023年3月9日 23:51:54
  • 转载请务必保留本文链接：https://go.coder-hub.com/75687002.html
  • data-wrangling
  • dataframe
  • r
  • tidyverse
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