在使用 rvest 抓取时输入缺失值的 NA [英] Inputting NA where there are missing values when scraping with rvest

问题描述

我想使用 rvest 抓取一个页面，该页面包含最近一次会议上的标题和运行时间，然后将这些值组合成一个 tibble

I want to use rvest to scrape a page which has titles and run times of talks at a recent conference and then combine the values into a tibble

library(tibble)
library(rvest)

url <- "https://channel9.msdn.com/Events/useR-international-R-User-conferences/useR-International-R-User-2017-Conference?sort=status&direction=desc&page=14"

title <- page %>% 
      html_nodes("h3 a") %>% 
      html_text()

length <- page %>% 
      html_nodes(".tile .caption") %>% 
      html_text()

df <- tibble(title,length)

如果您查看该页面，您会发现其中一个演讲没有任何价值 - 而在查看源代码中，此演讲没有 class="caption"

If you look at the page, you will see that for one of the talks there is no value - and in View source there is no class="caption" for this talk

有什么办法可以替换 NA 来显示缺失值?

Is there any way I can substitute an NA to show missing values?

推荐答案

最简单的方法是选择一个节点，每行都包含你想要的两个节点，然后遍历它们，拉出你想要的两个节点立刻.purrr::map_df 不仅可以方便地迭代，甚至可以将结果组合成一个漂亮的小标题:

The simplest way is to select a node that encloses both of the nodes you want for each row, then iterate over them, pulling out both of the nodes you want at once. purrr::map_df is handy for not only iterating, but even combining the results into a nice tibble:

library(rvest)
library(purrr)

url <- "https://channel9.msdn.com/Events/useR-international-R-User-conferences/useR-International-R-User-2017-Conference?sort=status&direction=desc&page=14"

page <- read_html(url)

df <- page %>% 
    html_nodes('article') %>%    # select enclosing nodes
    # iterate over each, pulling out desired parts and coerce to data.frame
    map_df(~list(title = html_nodes(.x, 'h3 a') %>% 
                     html_text() %>% 
                     {if(length(.) == 0) NA else .},    # replace length-0 elements with NA
                 length = html_nodes(.x, '.tile .caption') %>% 
                     html_text() %>% 
                     {if(length(.) == 0) NA else .}))

df
#> # A tibble: 12 x 2
#>                                                                                title   length
#>                                                                                <chr>    <chr>
#>  1                             Introduction to Natural Language Processing with R II 01:15:00
#>  2                                Introduction to Natural Language Processing with R 01:22:13
#>  3                                          Solving iteration problems with purrr II 01:22:49
#>  4                                             Solving iteration problems with purrr 01:32:23
#>  5                           Markov-Switching GARCH Models in R: The MSGARCH Package    15:55
#>  6                    Interactive bullwhip effect exploration using SCperf and Shiny    16:02
#>  7                             Actuarial and statistical aspects of reinsurance in R    14:15
#>  8                                                            Transformation Forests    16:19
#>  9                                                         Room 2.02 Lightning Talks    50:35
#> 10                                   R and Haskell: Combining the best of two worlds    14:45
#> 11 *GNU R* on a Programmable Logic Controller (PLC) in an Embedded-Linux Environment     <NA>
#> 12     Performance Benchmarking of the R Programming Environment on Knight's Landing    19:32

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