使用R从XML文件读取数据

从阅读开始,然后在StackOverflow上尝试一些与R中读取 XML文件相关的先前示例,似乎由于以下文件的“锯齿状”性质,我无法使用XPath相关方法.

https://www.dropbox.com/s/jz8sj2fifuobkva/Data.xml?oref=e&n=305307914

因此,似乎我需要使用xmlToList()和ldply()的组合来从以下文件中读取数据.

具体来说,对于文件中的所有20个事件(即event.1,event.2,… event.20),我想获得以下变量(结构化为)

> $moves $movement $clips $clip $data $event $begin(vector)
> $moves $movement $clips $clip $data $event $end(vector)
> $moves $movement $clips $clip $data $event $max $cells(data frame)
>如上所述,但$rollover $data $quant $cells,其中一个事件中有多个样本(n个数据帧)

基于其他StackOverflow示例代码(使用R v3.1.2)我试图读取“开始”数据如下： –

library(XML)
library(plyr)

datfile <- "D:/Data.xml"
xmlfile <- xmlTreeParse(datfile,useInternal = TRUE)
sampledata <- xmlToList(xmlfile)
startdata <- ldply(sampledata$movements$movement$clips$clip$data$event$begin)

当我这样做时,我只得到event.1中的第一个变量(0.240).我现在已经到了被困的地步,并且已经用尽了我对如何做到这一点的调查.

如果你愿意给xml2一个go,你可以从几行开始：

library(xml2)
library(magrittr)

# get a vector

doc <- read_xml("~/Dropbox/Data.xml")

doc %>%
  xml_find_all("//d1:event/d1:begin", ns=xml_ns(doc)) %>%
  xml_text() %>%
  as.numeric()

##  [1] 0.24 0.73 1.25 1.75 2.24 2.75 3.27 3.76 4.30 4.77 5.28 5.78 6.32 6.82
## [15] 7.34 7.85 8.37 8.86 9.39 9.89

# get data frames

library(stringr)

make_df <- function(txt) {

  txt %>%
    str_split("\n") %>% extract2(1) %>%
    str_trim() %>%
    textConnection() -> con

  dat <- read.table(con)
  close(con)

  dat

}

doc %>%
  xml_find_all("//d1:max/d1:cells", ns=xml_ns(doc)) %>%
  xml_text() %>%
  lapply(make_df) -> df_list

df_list[[1]]

##     V1   V2   V3   V4   V5   V6   V7   V8   V9 V10 V11 V12
## 1  0.0  0.0  1.5  3.5  3.0  1.5  0.0  0.0  0.0 0.0 0.0   0
## 2  0.0  1.0  5.5  8.5  7.0  3.5  2.0  2.0  1.0 0.0 0.0   0
## 3  0.0  3.0  9.0 13.0  9.0  4.0  3.0  3.5  2.5 1.0 0.0   0
## 4  0.0  4.5 11.0 14.0  9.0  4.0  3.0  4.0  4.0 2.0 0.0   0
## 5  0.0  4.0 10.5 12.0  7.5  4.0  3.0  4.0  4.5 3.0 0.0   0
## 6  0.0  4.5  8.5 10.0  8.0  7.5  6.5  4.5  4.0 2.5 0.0   0
## 7  2.0  8.0 14.5 16.0 14.0 13.5 13.0  9.5  5.5 2.5 0.0   0
## 8  3.5 12.0 20.0 20.5 18.0 18.0 18.0 14.5  9.0 4.0 1.5   0
## 9  4.5 12.5 20.5 21.0 18.0 18.0 18.5 16.0 11.5 6.5 2.5   0
## 10 4.5 12.0 19.0 20.0 17.5 17.5 18.0 16.5 12.5 7.5 3.5   0
## 11 3.5  9.5 15.5 16.5 15.0 14.5 14.5 14.0 11.5 8.0 4.0   1
## 12 2.0  6.5 10.0 12.0 11.0 11.0 12.0 12.0 10.5 7.5 4.0   0
## 13 1.5  4.5  6.5  7.0  7.0  7.0  8.0  9.0  8.0 6.5 3.5   0
## 14 1.0  4.0  5.5  5.5  5.5  5.5  6.0  6.0  6.0 4.5 2.5   0
## 15 1.5  4.5  6.0  5.5  5.5  5.5  5.5  5.5  5.5 4.0 2.0   0
## 16 2.0  5.0  7.0  7.0  6.0  6.0  6.0  6.0  5.5 4.0 1.5   0
## 17 2.5  5.5  7.5  7.5  7.0  7.0  6.5  6.5  5.5 4.0 1.5   0
## 18 2.0  5.5  7.0  7.5  7.5  7.5  7.5  6.5  5.5 3.5 0.0   0
## 19 2.5  5.5  7.5  8.0  7.5  8.0  7.5  6.5  5.0 2.5 0.0   0
## 20 2.0  5.0  6.5  7.5  7.5  8.0  7.5  6.5  4.5 2.0 0.0   0
## 21 1.5  4.0  6.0  7.5  8.5  8.5  8.0  6.0  3.5 1.0 0.0   0
## 22 1.0  3.5  6.5  8.5  9.5  9.5  8.0  5.5  3.0 0.0 0.0   0
## 23 0.0  4.0  8.0 11.0 12.5 11.0  8.5  5.5  2.5 0.0 0.0   0
## 24 0.0  4.5  9.5 13.5 14.5 12.0  8.5  5.5  2.0 0.0 0.0   0
## 25 0.0  5.5 13.0 17.5 17.0 14.5  9.5  5.5  1.5 0.0 0.0   0
## 26 0.0  6.5 16.0 21.0 19.5 15.5 10.0  5.0  1.0 0.0 0.0   0
## 27 0.0  7.0 17.0 22.5 21.0 16.0 10.0  5.0  0.0 0.0 0.0   0
## 28 0.0  7.0 17.5 22.5 20.5 15.5  9.0  3.5  0.0 0.0 0.0   0
## 29 0.0  5.5 14.5 20.5 18.5 14.0  8.0  2.5  0.0 0.0 0.0   0
## 30 0.0  3.5 10.0 14.5 14.0 10.0  5.0  1.0  0.0 0.0 0.0   0
## 31 0.0  1.5  5.5  8.5  8.0  5.5  2.5  0.0  0.0 0.0 0.0   0
## 32 0.0  0.0  0.0  2.5  2.5  0.0  0.0  0.0  0.0 0.0 0.0   0

length(df_list)

## [1] 20

# get the deeply nested ones

quant_cells <- function(node) {
  node %>%
    xml_find_all("./d1:data/d1:quant/d1:cells", ns=xml_ns(doc)) %>%
    xml_text() %>%
    lapply(make_df)
}

doc %>%
  xml_find_all("//d1:rollover", ns=xml_ns(doc)) %>%
  as_list() %>%
  lapply(quant_cells) -> quant_df_list

length(quant_df_list)

## [1] 20

length(quant_df_list[[1]])

## [1] 63

quant_df_list[[1]]

## [[1]]
##    V1  V2  V3  V4  V5 V6
## 1 0.0 0.0 0.0 0.0 0.0  0
## 2 0.0 0.0 0.2 0.0 0.0  0
## 3 0.0 0.5 1.7 0.5 0.0  0
## 4 0.5 2.7 3.4 2.3 0.3  0
## 5 2.3 4.3 4.4 3.0 0.4  0
## 6 3.2 4.8 4.8 3.3 0.4  0
## 7 2.2 4.1 3.8 2.3 0.3  0
## 8 0.3 1.4 1.4 0.4 0.0  0
## 
## [[2]]
##    V1  V2   V3   V4  V5  V6  V7  V8 V9
## 1 0.0 0.0  0.0  0.0 0.0 0.0 0.0 0.0  0
## 2 0.0 0.3  0.9  1.3 1.1 0.4 0.0 0.0  0
## 3 0.2 2.2  4.5  5.9 4.7 2.0 0.2 0.0  0
## 4 1.0 5.3  8.5  9.1 7.1 3.7 0.4 0.0  0
## 5 2.9 8.3 12.0 11.6 9.0 5.4 1.0 0.0  0
## 6 3.5 9.2 13.5 12.9 9.6 5.8 1.5 0.1  0
## 7 3.0 8.2 11.6 11.3 8.3 4.4 0.5 0.0  0
## 8 1.1 3.7  6.4  6.3 4.0 1.8 0.2 0.0  0
## 9 0.0 0.2  1.4  1.5 0.3 0.0 0.0 0.0  0
## ...
## (down to [[63]])