我正在從 sec 檔案中抓取一些資料。每個 xml 檔案都有基本的形式：
<ns1:infoTable>
<ns1:nameOfIssuer>ACCENTURE PLC IRELAND</ns1:nameOfIssuer>
<ns1:titleOfClass>SHS CLASS A</ns1:titleOfClass>
<ns1:cusip>G1151C101</ns1:cusip>
<ns1:value>47837</ns1:value>
<ns1:shrsOrPrnAmt>
<ns1:sshPrnamt>183135</ns1:sshPrnamt>
<ns1:sshPrnamtType>SH</ns1:sshPrnamtType>
</ns1:shrsOrPrnAmt>
<ns1:investmentDiscretion>SOLE</ns1:investmentDiscretion>
<ns1:votingAuthority>
<ns1:Sole>0</ns1:Sole>
<ns1:Shared>0</ns1:Shared>
<ns1:None>183135</ns1:None>
</ns1:votingAuthority>
</ns1:infoTable>
但是，有時檔案具有以下形式：
<infoTable>
<nameOfIssuer>2U INC</nameOfIssuer>
<titleOfClass>COM</titleOfClass>
<cusip>90214J101</cusip>
<value>340</value>
<shrsOrPrnAmt>
<sshPrnamt>8504</sshPrnamt>
<sshPrnamtType>SH</sshPrnamtType>
</shrsOrPrnAmt>
<investmentDiscretion>SOLE</investmentDiscretion>
<votingAuthority>
<Sole>8504</Sole>
<Shared>0</Shared>
<None>0</None>
</votingAuthority>
</infoTable>
所以標簽的唯一區別是添加了“ns1:”前綴。
在抓取資料時，我能夠找到像這樣的節點：
urll <- "https://www.sec.gov/Archives/edgar/data/1002152/000108514621000479/infotable.xml"
session %>%
nod(urll) %>%
scrape(verbose = FALSE) %>%
xml_ns_strip() %>%
xml_find_all('ns1:infoTable')
或者對于沒有 ns1: 前綴的備用標簽
urll <- "https://www.sec.gov/Archives/edgar/data/1002672/000106299321000915/form13fInfoTable.xml"
session %>%
nod(urll) %>%
scrape(verbose = FALSE) %>%
xml_ns_strip() %>%
xml_find_all('infoTable')
但是當回圈多個鏈接時，我不知道哪個 xml 檔案將具有哪個標簽。有沒有辦法通過使用“或”運算子指定節點或使用字串匹配查找標簽來獲取節點，以查找標簽中的特定文本“infoTable”？
我試過：
session %>%
nod(urll) %>%
scrape(verbose = FALSE) %>%
xml_ns_strip() %>%
xml_find_all(xpath = '//*[self::infoTable or self::ns1:infoTable]')
或者
session %>%
nod(urll) %>%
scrape(verbose = FALSE) %>%
xml_ns_strip() %>%
xml_find_all(xpath = "//*[contains(text(),'infoTable')]")
但兩種變化都不起作用。關于如何讓它作業的任何建議？
提前致謝。我正在使用禮貌、rvest、dplyr
uj5u.com熱心網友回復：
local-name()在您的 XPath 運算式中考慮。下面使用httr和新的 R 4.1.0 管道|>：
library(xml2)
library(httr)
url <- "https://www.sec.gov/Archives/edgar/data/1002152/000108514621000479/infotable.xml"
info_tables <- httr::GET(url, user_agent("Mozilla/5.0")) |>
httr::content(encoding="UTF-8") |>
xml2::xml_find_all(xpath = "//*[local-name()='infoTable']")
并構建資料框：
df_list <- lapply(info_tables, function(r) {
vals <- xml2::xml_children(r)
other_vals <- xml2::xml_find_all(r, "*") |>
xml2::xml_children()
child_df <- setNames(
c(xml2::xml_text(vals)),
c(xml2::xml_name(vals))
) |> rbind() |> data.frame()
grand_df <- setNames(
c(xml2::xml_text(other_vals)),
c(xml2::xml_name(other_vals))
) |> rbind() |> data.frame()
cbind.data.frame(child_df, grand_df)
})
final_df <- do.call(rbind.data.frame, df_list)
final_df
nameOfIssuer titleOfClass cusip value shrsOrPrnAmt investmentDiscretion votingAuthority sshPrnamt sshPrnamtType Sole Shared None
1 ACCENTURE PLC IRELAND SHS CLASS A G1151C101 47837 183135SH SOLE 00183135 183135 SH 0 0 183135
2 ALPHABET INC CAP STK CL A 02079K305 43695 24931SH SOLE 0024931 24931 SH 0 0 24931
3 APPLE INC COM 037833100 3229 24334SH SOLE 0024334 24334 SH 0 0 24334
4 BERKSHIRE HATHAWAY INC DEL CL A 084670108 2783 8SH SOLE 008 8 SH 0 0 8
5 CANADIAN NATL RY CO COM 136375102 218 1985SH SOLE 001985 1985 SH 0 0 1985
6 CHECK POINT SOFTWARE TECH LT ORD M22465104 45505 342375SH SOLE 00342375 342375 SH 0 0 342375
7 CHURCH & DWIGHT INC COM 171340102 42500 487221SH SOLE 00487221 487221 SH 0 0 487221
8 COGNIZANT TECHNOLOGY SOLUTIO CL A 192446102 46076 562243SH SOLE 00562243 562243 SH 0 0 562243
9 CVS HEALTH CORP COM 126650100 44311 648773SH SOLE 00648773 648773 SH 0 0 648773
10 DANAHER CORPORATION COM 235851102 44200 198974SH SOLE 00198974 198974 SH 0 0 198974
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