write_csv()即使在rstudio cloud中设置目录后也无法工作

发布于 2025-02-13 13:28:41 字数 1319 浏览 4 评论 0原文

无论我使用Wilter_CSV,包括目录更改,我似乎都无法显示此CSV文件以显示出现。我该如何(在Rstudio Cloud或本地程序中)执行此操作?在其他帖子中,我没有真正看到此问题的重复,也没有涉及错误。作为初学者的任何建议,都将不胜感激,谢谢。

  # read in the raw data
  init_updata <- readxl::read_excel("/cloud/project/secondalgdummy.xlsx")
  
  #--------------------------------------------------
  # PROCESSING
  #--------------------------------------------------
  processed_data <- init_updata %>%
    select_if(~!all(is.na(.))) %>% # remove NA cols
    dplyr::mutate(
      PAIN_SEVERITY = select(., starts_with("PAIN_INTENSITY")) %>% 
        rowMeans(na.rm = TRUE),
      N_BODYMAP_SEGMENTS = dplyr::pull(., BODYMAP_REGIONS_CSV) %>%
        count_segments() %>%
        replace_na(0),
      BODYMAP_REGIONS = dplyr::pull(., BODYMAP_REGIONS_CSV) %>%
        concat_regions(),
      PAIN_DURATION = PAIN_EXP_DURATION_YEARS*12 + PAIN_EXP_DURATION_MONTHS + PAIN_EXP_DURATION_DAYS/30
    ) %>%
    dplyr::select(MRN, all_of(all_vars))
  #--------------------------------------------------
  # MUNGING
  #--------------------------------------------------
  # not imputing data in this project --> remove patients with NA values
munged_data <- processed_data[complete.cases(select(processed_data, all_of(ind_vars))), ]
write_csv(munged_data, "full_munged_data.csv")
  

I can't seem to get this csv file to show up regardless of how many variations I use of write_csv, including directory changes. How can I do this (in either RStudio Cloud or the local program)? I did not truly see a duplicate of this problem in other posts, and no error is involved. Any advice as a beginner would be appreciated, thank you.

  # read in the raw data
  init_updata <- readxl::read_excel("/cloud/project/secondalgdummy.xlsx")
  
  #--------------------------------------------------
  # PROCESSING
  #--------------------------------------------------
  processed_data <- init_updata %>%
    select_if(~!all(is.na(.))) %>% # remove NA cols
    dplyr::mutate(
      PAIN_SEVERITY = select(., starts_with("PAIN_INTENSITY")) %>% 
        rowMeans(na.rm = TRUE),
      N_BODYMAP_SEGMENTS = dplyr::pull(., BODYMAP_REGIONS_CSV) %>%
        count_segments() %>%
        replace_na(0),
      BODYMAP_REGIONS = dplyr::pull(., BODYMAP_REGIONS_CSV) %>%
        concat_regions(),
      PAIN_DURATION = PAIN_EXP_DURATION_YEARS*12 + PAIN_EXP_DURATION_MONTHS + PAIN_EXP_DURATION_DAYS/30
    ) %>%
    dplyr::select(MRN, all_of(all_vars))
  #--------------------------------------------------
  # MUNGING
  #--------------------------------------------------
  # not imputing data in this project --> remove patients with NA values
munged_data <- processed_data[complete.cases(select(processed_data, all_of(ind_vars))), ]
write_csv(munged_data, "full_munged_data.csv")
  

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