如何将 PubMed 中的网格写入数据框

How to write the Mesh from PubMed into a data frame

我最近下载了 RISMed 软件包,从 PubMed 下载了不到 500,000 篇文章摘要,我正在尝试将此数据输入数据框。我在尝试包含网格数据时出现问题,我收到错误消息

'Error in (function (..., row.names = NULL, check.rows = FALSE, check.names = TRUE, : arguments imply differing number of rows:'

有没有办法将这些信息嵌套到数据框中进行分析?

RCT_topic <- 'randomized clinical trial'
RCT_query <- EUtilsSummary(RCT_topic, mindate=2016, maxdate=2017, retmax=100)
summary(RCT_query)
RCT_records <- EUtilsGet(RCT_query)

RCT_data <- data.frame('PMID'=PMID(RCT_records), 
                       'Title'=ArticleTitle(RCT_records), 
                       'Abstract'=AbstractText(RCT_records), 
                       'YearPublished'=YearPubmed(RCT_records), 
                       'Month.Published'=MonthPubmed(RCT_records), 
                       'Country'=Country(RCT_records), 
                       'Grant'=GrantID(RCT_records), 
                       'Acronym'=Acronym(RCT_records), 
                       'Agency'=Agency(RCT_records),
                       'Mesh'=Mesh(RCT_records))

考虑使用 tibble:

library(RISmed)
library(dplyr) # tibble and other functions

RCT_topic <- 'randomized clinical trial'
RCT_query <- EUtilsSummary(RCT_topic, mindate=2016, maxdate=2017, retmax=100)
summary(RCT_query)
RCT_records <- EUtilsGet(RCT_query)

RCT_data <- data_frame('PMID'=PMID(RCT_records),
                       'Title'=ArticleTitle(RCT_records),
                       'Abstract'=AbstractText(RCT_records),
                       'YearPublished'=YearPubmed(RCT_records),
                       'Month.Published'=MonthPubmed(RCT_records),
                       'Country'= Country(RCT_records),
                       'Grant' =GrantID(RCT_records),
                       'Acronym' =Acronym(RCT_records),
                       'Agency' =Agency(RCT_records),
                       'Mesh'=Mesh(RCT_records))

Mesh 列现在是数据帧列表:

select(RCT_data, PMID, Mesh)
# # A tibble: 100 x 2
#    PMID     Mesh                 
#    <chr>    <list>               
#  1 29288775 <data.frame [21 × 2]>
#  2 29288545 <data.frame [19 × 2]>
#  3 29288510 <data.frame [15 × 2]>
#  4 29288507 <data.frame [19 × 2]>
#  5 29288478 <data.frame [16 × 2]>
#  6 29288309 <data.frame [19 × 2]>
#  7 29288191 <data.frame [11 × 2]>
#  8 29288190 <data.frame [23 × 2]>
#  9 29288184 <data.frame [21 × 2]>
# 10 29288175 <data.frame [12 × 2]>
# # ... with 90 more rows