我正在尝试从此页面中提取所有选项卡中所有值的值。 http://www.imd.gov.in/section/hydro/dynamic/rfmaps/weekrain.htm
我首先尝试下载为excel。但那是不可能的。我只能将其下载为文本文件。如果我尝试直接从网页上阅读，我会得到原始的html页面。我被困在如何提取这些值。请找到我尝试过的代码。
library(RCurl)
require(XML)
url = "http://www.imd.gov.in/section/hydro/dynamic/rfmaps/weekrain.htm"
download.file(url = url, destfile = "E:\\indiaprecip")
答案 0 :(得分：1)
只需使用XML中的函数“htmlTreeParse”
library(XML)
html <- htmlTreeParse("http://www.imd.gov.in/section/hydro/dynamic/rfmaps/weekrain.htm",
useInternalNodes = T)
xpathSApply(html, "//meta/@name")
但在你的情况下，你有另一个问题。您要访问的数据位于html框架中。以下代码可以帮助您阅读这些数据：
library(XML)
library(RCulr)
url <- "http://www.imd.gov.in/section/hydro/dynamic/rfmaps/weekrain.htm"
html <- htmlTreeParse(url, useInternalNodes = T)
frameUrl <- paste("http://www.imd.gov.in/section/hydro/dynamic/rfmaps/",
xpathSApply(html, "//frame[1]/@src"),
sep = "")
htmlWithData = getURL(frameUrl,
httpheader = c("User-Agent" = "RCurl",
"Referer" = url))
dataXml <- htmlTreeParse(htmlWithData, isURL = F, useInternalNodes = T)
xpathSApply(dataXml, "//body/table")
答案 1 :(得分：1)
唉。 Excel - ＆gt; HTML + iframe。以下内容可帮助您入门。无论您使用何种方法，您都必须在刮擦后进行大量处理。我没有显示它的使用，但htmltab包也可以在这里提供帮助。
library(xml2) # devtools::install_github("hadley/xml2")
library(rvest) # devtools::install_github("hadley/rvest")
library(httr)
library(magrittr)
base_url <- "http://www.imd.gov.in/section/hydro/dynamic/rfmaps/weekrain_files"
# Get all the state sheet URLs --------------------------------------------
state_sheets <- read_html(sprintf("%s/%s", base_url, "tabstrip.htm"))
state_sheets %>%
html_nodes(xpath="//a[@target='frSheet']") %>%
html_attr("href") -> state_links
state_sheets %>%
html_nodes(xpath="//a[@target='frSheet']") %>%
html_text() -> state_names
state_links
## [1] "sheet001.htm" "sheet002.htm" "sheet003.htm" "sheet004.htm"
## [5] "sheet005.htm" "sheet006.htm" "sheet007.htm" "sheet008.htm"
## [9] "sheet009.htm" "sheet010.htm" "sheet011.htm" "sheet012.htm"
## [13] "sheet013.htm" "sheet014.htm" "sheet015.htm" "sheet016.htm"
## [17] "sheet017.htm" "sheet018.htm" "sheet019.htm" "sheet020.htm"
## [21] "sheet021.htm" "sheet022.htm" "sheet023.htm" "sheet024.htm"
## [25] "sheet025.htm" "sheet026.htm" "sheet027.htm" "sheet028.htm"
## [29] "sheet029.htm" "sheet030.htm" "sheet031.htm" "sheet032.htm"
## [33] "sheet033.htm" "sheet034.htm" "sheet035.htm"
state_names
## [1] "A & N ISLAND" "ANDHRA PRADESH" "ARUNACHAL PRADESH"
## [4] "ASSAM" "BIHAR" "CHANDIGARH"
## [7] "CHHATTISGARH" "DELHI" "DIU"
## [10] "DNH & DAMAN" "GOA" "GUJARAT"
## [13] "HARYANA" "HIMACHAL PRADESH" "JAMMU & KASHMIR"
## [16] "JHARKHAND" "KARNATAKA" "KERALA"
## [19] "LAKSHADWEEP" "MADHYA PRADESH" "MAHARASHTRA"
## [22] "MANIPUR" "MEGHALAYA" "MIZORAM"
## [25] "NAGALAND" "ORISSA" "PONDICHERRY"
## [28] "PUNJAB" "RAJASTHAN" "SIKKIM"
## [31] "TAMILNADU" "TRIPURA" "UTTAR PRADESH"
## [34] "UTTARAKHAND" "WEST BENGAL"
# Get one page ------------------------------------------------------------
# the referer was necessary for me. ymmv
rain <- html_session(sprintf("%s/%s", base_url, state_links[2]),
add_headers(Referer="http://www.imd.gov.in/section/hydro/dynamic/rfmaps/weekrain_files/tabstrip.htm"))
# Extract whole table (ugly) ----------------------------------------------
# this will require _alot_ of cleanup code
rain %>% html_nodes("table") %>% html_table() %>% extract2(1) %>% head(10)
## X1 X2
## 1
## 2 To view the\r\n Districtwise Rainfall of another State, <NA>
## 3 Click the desired\r\n STATE tab on the strip at the bottom <NA>
## 4 <NA>
## 5 <NA>
## 6 DISTRICTWISE RAINFALL\r\n DISTRIBUTION <NA>
## 7
## 8 <NA>
## 9 STATE/UT/MET.SUBDIVISION <NA>
## 10 DISTRICT\r\n (NAME) <NA>
## X3 X4 X5 X6 X7 X8 X9
## 1 NA
## 2 <NA> <NA> <NA> Back to Rainfall Statistics <NA> NA
## 3 <NA> <NA> <NA> <NA> <NA> NA
## 4 <NA> <NA> <NA> <NA> <NA> <NA> NA
## 5 <NA> <NA> <NA> <NA> <NA> <NA> NA
## 6 <NA> <NA> <NA> <NA> <NA> <NA> NA
## 7 16.07.2015 TO 22.07.2015 NA
## 8 <NA> <NA> <NA> NA
## 9 <NA> ACTUAL NORMAL %DEP CAT. NA
## 10 (mm) (mm) NA
# Extract by column -------------------------------------------------------
# painstaking and it may be less work to cleanup the table
rain %>% html_nodes("td.xl88") %>% html_text()
## [1] "East Godavary" "Guntur" "Krishna" "Nellore"
## [5] "Prakasam" "Srikakulam" "Vishakhapatnam" "Vizianagaram"
## [9] "West Godavary" "Adilabad" "Hyderabad" "Karimnagar"
## [13] "Khamman" "Mahabubnagar" "Medak" "Nalgonda"
## [17] "Nizamabad" "Rangareddy" "Warangal" "Anantapur"
## [21] "Chittor" "Cuddapah" "Kurnool"
rain %>% html_nodes("td[class='xl85'][x\\:num='']") %>% html_text()
## [1] "43.1" "35.8" "48.2" "22.1" "26.5" "46.8" "44.3" "42.5" "52.4" "16.8"
## [11] "26.2" "26.3" "25.4" "0.0" "0.0" "0.0" "54.8" "0.0" "0.0" "0.0"
## [21] "73.9" "43.1" "53.2" "41.9" "64.7" "44.1" "62.1"
rain %>% html_nodes("td[class='xl85'][x\\:num!='']") %>% html_text()
## [1] "94.3" "E" "50.6" "E" "44.8" "N" "8.2" "S" "10.4" "S"
## [11] "53.2" "N" "44.5" "N" "43.3" "N" "82.7" "E" "" ""
## [21] "9.8" "D" "16.0" "D" "8.9" "S" "6.7" "S" "25.2" "D"
## [31] "59.3" "D" "7.8" "S" "34.2" "D" "" "" "16.1" "S"
## [41] "27.6" "D" "13.2" "S" "17.1" "S" ""