将宽表格转换为长表格在R中

huangapple
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英文:

convert wide table to long in R

问题

我有一个类似以下的数据集：

  1. groupA <- rbinom(n=50,size=1,prob=0.5)
  2. groupB <- rbinom(n=50,size=1,prob=0.5)
  3. groupC <- rbinom(n=50,size=1,prob=0.5)
  4. groupD <- rbinom(n=50,size=1,prob=0.5)
  5. dtTest <- cbind(groupA, groupB, groupC, groupD)

其中，0表示"no"，1表示"yes"。

现在，我想创建一个表格，包括一列Group和另一列answer，指示是或否。

如何实现这个目标？

我尝试使用melt函数和data.table的分组，但一直出现错误。

英文:

I have a dataset that look something like this:

  1. groupA &lt;- rbinom(n=50,size=1,prob=0.5)
  2. groupB &lt;- rbinom(n=50,size=1,prob=0.5)
  3. groupC &lt;- rbinom(n=50,size=1,prob=0.5)
  4. groupD &lt;- rbinom(n=50,size=1,prob=0.5)
  5. dtTest &lt;- cbind(groupA, groupB, groupC, groupD)

where 0 means "no" and 1 means "yes".

Now, i want to create a table with a column Group and another column answer, stating yes or no.

How can this be done ?

I tried the melt function and data.table group by, but keep getting error.

答案1

得分: 1

尝试使用 tidyverse / tidyr：

  1. library(tidyverse)
  2. library(tidyr)
  3. df <- dtTest %>% as_tibble() %>% 
  4.   pivot_longer(everything(), names_to = "groups", values_to = "values") %>% 
  5.   mutate(answer = ifelse(values == 0, "no", "yes"))
英文:

Try tidyverse / tidyr:

  1. library(tidyverse)
  2. library(tidyr)
  3. df &lt;- dtTest %&gt;% as_tibble() %&gt;% 
  4.   pivot_longer(everything(), names_to = &quot;groups&quot;, values_to = &quot;values&quot;) %&gt;% 
  5.   mutate(answer = ifelse(values == 0, &quot;no&quot;, &quot;yes&quot; ))

答案2

得分: 0

We may use stack on the data.frame converted - cbind by default returns a matrix and not a data.frame. Instead, we may directly use data.frame(groupA, groupB, ...)

  1. out <- stack(as.data.frame(dtTest))[2:1]
  2. names(out) <- c("Group", "answer")
  3. out$answer <- c("no", "yes")[out$answer + 1]

-output

  1. > head(out)
  2.    Group answer
  3. 1 groupA     no
  4. 2 groupA     no
  5. 3 groupA    yes
  6. 4 groupA     no
  7. 5 groupA     no
  8. 6 groupA     no

For data.table::melt, we may specify the measure as the column names, (after converting to data.table - as.data.table)

  1. library(data.table)
  2. melt(as.data.table(dtTest), measure = colnames(dtTest), 
  3.    variable.name = "Group", value.name = "answer")[, 
  4.   answer := c("no", "yes")[answer + 1]][]

-output

  1.    Group answer
  2.   1: groupA     no
  3.   2: groupA     no
  4.   3: groupA    yes
  5.   4: groupA     no
  6.   5: groupA     no
  7.  ---              
  8. 196: groupD    yes
  9. 197: groupD    yes
  10. 198: groupD    yes
  11. 199: groupD    yes
  12. 200: groupD     no
英文:

We may use stack on the data.frame converted - cbind by default returns a matrix and not a data.frame. Instead, we may directly use data.frame(groupA, groupB, ...)

  1. out &lt;- stack(as.data.frame(dtTest))[2:1]
  2. names(out) &lt;- c(&quot;Group&quot;, &quot;answer&quot;)
  3. out$answer &lt;- c(&quot;no&quot;, &quot;yes&quot;)[out$answer + 1]

-output

  1. &gt; head(out)
  2.    Group answer
  3. 1 groupA     no
  4. 2 groupA     no
  5. 3 groupA    yes
  6. 4 groupA     no
  7. 5 groupA     no
  8. 6 groupA     no

For data.table::melt, we may specify the measure as the column names, (after converting to data.table - as.data.table)

  1. library(data.table)
  2. melt(as.data.table(dtTest), measure = colnames(dtTest), 
  3.    variable.name = &quot;Group&quot;, value.name = &quot;answer&quot;)[, 
  4.   answer := c(&quot;no&quot;, &quot;yes&quot;)[answer + 1]][]

-output

  1.    Group answer
  2.   1: groupA     no
  3.   2: groupA     no
  4.   3: groupA    yes
  5.   4: groupA     no
  6.   5: groupA     no
  7.  ---              
  8. 196: groupD    yes
  9. 197: groupD    yes
  10. 198: groupD    yes
  11. 199: groupD    yes
  12. 200: groupD     no

huangapple
  • 本文由 发表于 2023年3月4日 03:08:49
  • 转载请务必保留本文链接：https://go.coder-hub.com/75630990.html
  • data.table
  • longtable
  • melt
  • r
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