dplyr case_when跨组时

如何解决dplyr case_when跨组时

我有df

var request = service.Files.Get(item.Id);
var rootfolder = uploadPathList.FirstOrDefault(i =>i.Id == parentId);
MemoryStream stream1 = new MemoryStream();
string FolderPath = Environment.CurrentDirectory + "/";
// Add a handler which will be notified on progress changes.
// It will notify on each chunk download and when the
// download is completed or failed.
request.MediaDownloader.ProgressChanged += (Google.Apis.Download.IDownloadProgress progress) =>{
  switch (progress.Status) {
  case DownloadStatus.Downloading:
    {
      Console.WriteLine(progress.BytesDownloaded);

      break;
    }
  case DownloadStatus.Completed:
    {
      apiService.FileUpload(stream1,item.Name,rootfolder.Path);

      using(System.IO.FileStream file = new FileStream(FolderPath + "/" + item.Name,FileMode.Create,FileAccess.ReadWrite)) {
        if (file.Length > 0) {
          stream1.WriteTo(file);
        }

      }

      Console.WriteLine("Download complete.");

      break;
    }
  case DownloadStatus.Failed:
    {
      Console.WriteLine("Download failed.");
      break;
    }
  }
};

apiService.FileUpload(stream1,rootfolder.Path);
//DownloadFromDrive(service,item.Id,)
request.Download(stream1);

和两个向量：

df = data.frame(
    group = c(rep("A",3),rep("B",3)),vt = c("SO:0001574","SO:0001619","SO:0001821")
    )

我想产生一个输出：

tier_1 = c("SO:0001574","SO:0001575")
tier_2 = c("SO:0001821","SO:0001822")

即我想生成第三列ct，它根据tier_1或tier_2中是否存在vt列来填充，以便给定组中的所有行都填充有该层类型。

我尝试过：

  group         vt     ct
1     A SO:0001574 tier_1
2     A SO:0001619 tier_1
3     A SO:0001619 tier_1
4     B SO:0001619 tier_2
5     B SO:0001619 tier_2
6     B SO:0001821 tier_2

但这仅填充单个行，而不填充组中的所有行：

df %>%
    dplyr::group_by(group) %>% 
    dplyr::mutate(tier = dplyr::case_when(
        vt %in% tier_1 ~ "tier_1",vt %in% tier_2 ~ "tier_2"))

解决方法

在any中包装代码，以使每个组获得一个逻辑值：

library(dplyr)

df %>%
 group_by(group) %>% 
 mutate(tier = case_when(
                any(vt %in% tier_1) ~ "tier_1",any(vt %in% tier_2) ~ "tier_2"))

#  group vt         tier  
#  <chr> <chr>      <chr> 
#1 A     SO:0001574 tier_1
#2 A     SO:0001619 tier_1
#3 A     SO:0001619 tier_1
#4 B     SO:0001619 tier_2
#5 B     SO:0001619 tier_2
#6 B     SO:0001821 tier_2

,

在您描述了第一步之后，您还可以在fill()中使用{tidyr}：

library(tidyr)
library(dplyr)

df = data.frame(
  group = c(rep("A",3),rep("B",3)),vt = c("SO:0001574","SO:0001619","SO:0001821")
)
tier_1 = c("SO:0001574","SO:0001575")
tier_2 = c("SO:0001821","SO:0001822")

df %>%
  group_by(group) %>% 
  mutate(tier = case_when(
    vt %in% tier_1 ~ "tier_1",vt %in% tier_2 ~ "tier_2")) %>%
  fill(tier,.direction = "updown") %>%
  ungroup()

# A tibble: 6 x 3
# Groups:   group [2]
#  group vt         tier  
#  <chr> <chr>      <chr> 
#1 A     SO:0001574 tier_1
#2 A     SO:0001619 tier_1
#3 A     SO:0001619 tier_1
#4 B     SO:0001619 tier_2
#5 B     SO:0001619 tier_2
#6 B     SO:0001821 tier_2