您似乎意识到表内容来自JSON，通常这意味着它是由javascript获取的，并且不包含在页面源代码中，即不可能仅通过使用在支持javascript的浏览器中工作的相同选择器和XPath来提取rvest表内容。
将JSON重新排列成类似于页面上呈现的表格的东西，可以通过以下方式实现：

library(jsonlite)
library(dplyr)
library(purrr)
library(tidyr)

"https://www.topuniversities.com/rankings/endpoint?nid=3846211&page=0&items_per_page=15&tab=indicators&region=&countries=&cities=&search=&star=&sort_by=&order_by=" %>% 
  fromJSON() %>% 
  pluck("score_nodes") %>% 
  # fromJSON() transforms scores into list of 5x4 data.frames
  # selecting relevant columns and pivoting wider turns those into 1x5 data.frames,
  # single row per parent data.frame row, `scores` will remain a nested column for now
  mutate(scores = map(scores, 
                      \(x) select(x, indicator_name, score) %>% 
                        pivot_wider(names_from = indicator_name, values_from = score))) %>% 
  select(title, region, country, city, overall_score, rank_display, scores) %>% 
  # extract all 5 score columns
  unnest(scores)

结果：

#> # A tibble: 15 × 11
#>    title   region country city  overall_score rank_display `Academic Reputation`
#>    <chr>   <chr>  <chr>   <chr> <chr>         <chr>        <chr>                
#>  1 "Harva… North… United… Camb… 98.2          1            100                  
#>  2 "Unive… Europe United… Camb… 96.9          2            99.2                 
#>  3 "Unive… Europe United… Oxfo… 96.8          3            99.4                 
#>  4 "Stanf… North… United… Stan… 91.6          4            93.7                 
#>  5 "Unive… North… United… Berk… 91.5          5            95.4                 
#>  6 "Yale … North… United… New … 88.9          6            94.5                 
#>  7 "Colum… North… United… New … 88.6          =7           92.5                 
#>  8 "New Y… North… United… New … 88.6          =7           93.8                 
#>  9 "Unive… North… United… Los … 88.3          9            92.5                 
#> 10 "The U… Europe United… Edin… 87.8          10           92.2                 
#> 11 "UCL"   Europe United… Lond… 87            11           90.3                 
#> 12 "Massa… North… United… Camb… 86.6          12           86.3                 
#> 13 "Princ… North… United… Prin… 86            13           92.4                 
#> 14 "Unive… North… United… Chic… 85.9          14           93.3                 
#> 15 "Unive… North… Canada  Toro… 85.2          15           89                   
#> # ℹ 4 more variables: `Employer Reputation` <chr>, `Citations per Paper` <chr>,
#> #   `H-index Citations` <chr>, `International Research Network` <chr>

创建于2023-03-23带有reprex v2.0.2
请注意，API调用仅返回前15条记录，请随意调整URL中的items_per_page参数。