【问题标题】:Splitting column text by delimiter into multiple different columns in R通过分隔符将列文本拆分为R中的多个不同列
【发布时间】:2022-01-17 02:37:56
【问题描述】:

我有以下问题。我必须将下面的文本分成单独的列。数据是通过网络抓取提取的,我需要对其进行转换以进行分析。例如,我复制了一行,我只需要 "id":357 和 "slug":"journalism/audio" 作为信息。你知道我怎样才能在 R 中转换它吗?下面的代码来自df栏:

{"id":357,"name":"Audio","analytics_name":"Audio","slug":"journalism/audio","position":1,"parent_id":13,"parent_name":"Journalism","color":1228010,"urls":{"web":{"discover":"http://www.kickstarter.com/discover/categories/journalism/audio"}}}

A screenshot sample table of the data I want to transform

【问题讨论】:

    标签: r etl reshape


    【解决方案1】:

    以这样的字符串开头

    stri
    [1] "\"id\":357,\"name\":\"Audio\",\"analytics_name\":\"Audio\",\"slug\":\"journalism/audio\",\"position\":1,\"parent_id\":13,\"parent_name\":\"Journalism\",\"color\":1228010,\"urls\":{\"web\":{\"discover\":\"http://www.kickstarter.com/discover/categories/journalism/audio"
    

    先将strsplit字符串用逗号分块并去掉引号

    d <- gsub( "\"","", strsplit(stri, ",")[[1]] )
    [1] "id:357"
    [2] "name:Audio"
    [3] "analytics_name:Audio"
    [4] "slug:journalism/audio"
    [5] "position:1"
    [6] "parent_id:13"
    [7] "parent_name:Journalism"
    [8] "color:1228010"
    [9] "urls:{web:{discover:http://www.kickstarter.com/discover/categories/journalism/audio"
    

    最后构建数据框

    dat <- data.frame( strsplit( d[grep("^id|^slug",d)], ":" ) )[2,]
    
    colnames( dat ) <- data.frame( strsplit( d[grep("^id|^slug",d)], ":" ) )[1,]
    dat
       id             slug
    2 357 journalism/audio
    

    数据

    stri <- "\"id\":357,\"name\":\"Audio\",\"analytics_name\":\"Audio\",\"slug\":\"journalism/audio\",\"position\":1,\"parent_id\":13,\"parent_name\":\"Journalism\",\"color\":1228010,\"urls\":{\"web\":{\"discover\":\"http://www.kickstarter.com/discover/categories/journalism/audio"
    

    【讨论】:

    • 谢谢,该解决方案适用于我的桌子。
    【解决方案2】:

    离开您在此处提供的一行数据,可能是这样的吗?

    library(magrittr)
    library(stringr)
    library(tidyr)
    library(dplyr)
    
    #Toy data.
    df <- data.frame(category = '{"id":357,"name":"Audio","analytics_name":"Audio","slug":"journalism/audio","position":1,"parent_id":13,"parent_name":"Journalism","color":1228010,"urls":{"web":{"discover":"http://www.kickstarter.com/discover/categories/journalism/audio"}}}')
    df[2, ] <- df[1, ] 
    
    
    df %>% 
      mutate(ucol = row_number()) %>%
      separate_rows(category, sep = ",") %>% 
      mutate(category = str_replace_all(category, '[\\"\\{\\}]', "")) %>% 
      filter(str_detect(category, "^id|^slug")) %>%
      separate(category, sep = ":", into = c("key", "val")) %>%
      pivot_wider(names_from = key, values_from = val)
    
    # # A tibble: 2 × 3
    #    ucol id    slug            
    #   <int> <chr> <chr>           
    # 1     1 357   journalism/audio
    # 2     2 357   journalism/audio
    

    【讨论】:

    • 谢谢,这个解决方案对我很有帮助。未来我会努力提供更好的数据进行测试。您的代码帮助我建立了使用管道并将数据转换为有意义信息的知识。
    • @user16268585 不客气!!
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