将具有多列的数据重塑为长格式。

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英文:

Reshape data with multiple columns to long format

问题

我相当确定，类似这样的问题以前已经被问过，但我找不到任何答案。

这是我的数据集：

  1. data.frame(Group = c("a", "b"), 
  2.            MEAN_A = 1:2, 
  3.            MEAN_B = 3:4, 
  4.            MED_A = 5:6, 
  5.            MED_B = 7:8) 
  6.   Group MEAN_A MEAN_B MED_A MED_B
  7. 1     a      1      3     5     7
  8. 2     b      2      4     6     8

我想要的是：

  1. data.frame(Group = c("a", "a", "b", "b"), 
  2.            Name = c("MEAN", "MED", "MEAN", "MED"),
  3.            Value_A = c(1, 5, 2, 6),
  4.            Value_B = c(3, 7, 4, 8))
  5.   Group Name Value_A Value_B
  6. 1     a MEAN       1       3
  7. 2     a  MED       5       7
  8. 3     b MEAN       2       4
  9. 4     b  MED       6       8

所以我想保留变量Group，并有一个新的列告诉我原始变量是来自MEAN还是MED，以及两列值A和B，最初在MEAN或MED之后的变量名中。

我已经尝试过pivot_longer，甚至使用了模式，但是我无法获得我期望的输出。

英文:

I'm pretty sure, that a question like this was asked before but I cannot find any.

This is my dataset:

  1. data.frame(Group = c("a", "b"), 
  2.            MEAN_A = 1:2, 
  3.            MEAN_B = 3:4, 
  4.            MED_A = 5:6, 
  5.            MED_B = 7:8) 
  6.   Group MEAN_A MEAN_B MED_A MED_B
  7. 1     a      1      3     5     7
  8. 2     b      2      4     6     8

What I want is the following:

  1. data.frame(Group = c("a", "a", "b", "b"), 
  2.            Name = c("MEAN", "MED", "MEAN", "MED"),
  3.            Value_A = c(1, 5, 2, 6),
  4.            Value_B = c(3, 7, 4, 8))
  5.   Group Name Value_A Value_B
  6. 1     a MEAN       1       3
  7. 2     a  MED       5       7
  8. 3     b MEAN       2       4
  9. 4     b  MED       6       8

So I want to keep the variable Group and have a new column which tells me, if the original variable was from MEAN or MED and two columns with the Values of A and B, that where initially in the variable names after MEAN or MED.

I've already tried pivot_longer, even with patterns, but I'm not able to get my desired output.

答案1

得分: 1

以下是翻译好的代码部分：

第一种方法：

  1. 选择组和"mean"列，将均值重命名为"Value_"，添加"mean"标识符。
  2. 选择组和"med"列，将中位数重命名为"Value_"，添加"med"标识符。
  3. 绑定这些框架，按"Group"排序：
  5. df %>%
  6.   select(1:3) %>%
  7.   rename_with(~gsub(pattern = "MEAN", replacement = "Value", .), .cols = starts_with("MEAN")) %>%
  8.   mutate(Name = "MEAN") %>%
  9.   rbind(df %>%
  10.               select(c(1,4,5)) %>%
  11.               rename_with(~gsub(pattern = "MED", replacement = "Value", .), .cols = starts_with("MED")) %>%
  12.               mutate(Name = "MED")) %>%
  13.   select(Group, Name, Value_A, Value_B) %>%
  14.   arrange(Group)

结果如下：

  1.   Group Name Value_A Value_B
  2. 1     a MEAN       1       3
  3. 2     a  MED       5       7
  4. 3     b MEAN       2       4
  5. 4     b  MED       6       8

编辑：另一种整洁的方法：

  1. df %>% 
  2.   pivot_longer(cols = any_of(c(ends_with("_A"), ends_with("_B"))),
  3.                names_to = c("Name", ".value"),
  4.                names_sep = "_") %>%
  5.   rename(Value_A = A, Value_B = B)

结果如下：

  1. # A tibble: 4 × 4
  2.   Group Name  Value_A Value_B
  3. 1 a     MEAN        1       3
  4. 2 a     MED         5       7
  5. 3 b     MEAN        2       4
  6. 4 b     MED         6       8

请注意，这是您提供的代码的翻译版本，没有其他附加内容。

英文:

Here's one approach:

Select the group and "mean" columns, rename the means to "Value_", add a "mean" identifier.
Select the group and "med" columns, rename the meds to "Value_", add a "med" identifier.
bind the frames together, sort by "Group":

  1. df %>% select(1:3) %>%
  2.   rename_with(~gsub(pattern = "MEAN", replacement = "Value", .), .cols = starts_with("MEAN")) %>%
  3.   mutate(Name = "MEAN") %>%
  4.   rbind(df %>%
  5.               select(c(1,4,5)) %>% 
  6.               rename_with(~gsub(pattern = "MED", replacement = "Value", .), .cols = starts_with("MED")) %>%
  7.               mutate(Name = "MED")) %>%
  8.   select(Group, Name, Value_A, Value_B) %>%
  9.   arrange(Group)

gives

  1.   Group Name Value_A Value_B
  2. 1     a MEAN       1       3
  3. 2     a  MED       5       7
  4. 3     b MEAN       2       4
  5. 4     b  MED       6       8

Edit: another tidy approach:

  1. df %>% 
  2.   pivot_longer(cols = any_of(c(ends_with("_A"), ends_with("_B"))),
  3.                names_to = c("Name", ".value"),
  4.                names_sep = "_") %>%
  5.   rename(Value_A = A, Value_B = B)
  7. # A tibble: 4 × 4
  8.   Group Name  Value_A Value_B
  9.   <chr> <chr>   <int>   <int>
  10. 1 a     MEAN        1       3
  11. 2 a     MED         5       7
  12. 3 b     MEAN        2       4
  13. 4 b     MED         6       8

huangapple
  • 本文由 发表于 2023年7月6日 16:31:27
  • 转载请务必保留本文链接：https://go.coder-hub.com/76626940.html
  • pivot-table
  • r
  • reshape
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