从XML属性到数据。

时间:2023-02-02 22:55:39

I have a XML that contains data like this:

我有一个包含如下数据的XML:

<?xml version="1.0" encoding="utf-8"?>
<posts>
  <row Id="1" PostTypeId="1" 
       AcceptedAnswerId="15" CreationDate="2010-07-19T19:12:12.510" Score="27" 
       ViewCount="1647" Body="some text;" OwnerUserId="8" 
       LastActivityDate="2010-09-15T21:08:26.077" 
       Title="title" AnswerCount="5" CommentCount="1" FavoriteCount="17" />
[...]

(The dataset is a dump from stats.stackexchange.com)

(数据集是stats.stackexchange.com提供的转储)

How to get a data.frame with the attributes "Id" and "PostTypeId"?

如何获得具有“Id”和“PostTypeId”属性的data.frame ?

I have been trying with the XML library but I get to a point where I don't know how to unwrap the values:

我一直在尝试使用XML库,但到了一个我不知道如何展开值的地步:

library(XML)

xml <- xmlTreeParse("Posts.xml",useInternalNode=TRUE)
types <- getNodeSet(xml, '//row/@PostTypeId')

> types[1]
[[1]]
PostTypeId 
       "1" 
attr(,"class")
[1] "XMLAttributeValue"

Which would be the proper R way of getting a projection of those two columns from the XML into a data.frame?

从XML将这两列投影到data.frame的正确方法是什么?

2 个解决方案

#1


2  

Using rvest (which is a wrapper around xml2) you can do it as follows:

使用rvest(它是xml2的包装),您可以按照以下方式进行:

require(rvest)
require(magrittr)
doc <- xml('<posts>
  <row Id="1" PostTypeId="1" 
AcceptedAnswerId="15" CreationDate="2010-07-19T19:12:12.510" Score="27" 
ViewCount="1647" Body="some text;" OwnerUserId="8" 
LastActivityDate="2010-09-15T21:08:26.077" 
Title="title" AnswerCount="5" CommentCount="1" FavoriteCount="17" />
</posts>')

rows <- doc %>% xml_nodes("row")
data.frame(
  Id = rows %>% xml_attr("id"),
  PostTypeId = rows %>% xml_attr("posttypeid")
)

Resulting in:

导致:

  Id PostTypeId
1  1          1

If you take Comments.xml
with

如果你把评论。xml与

data.frame(
  Id = rows %>% xml_attr("id"),
  PostTypeId = rows %>% xml_attr("postid"),
  score = rows %>% xml_attr("score")
)

You receive:

你收到:

> head(dat)
  Id PostTypeId score
1  1          3     5
2  2          5     0
3  3          9     0
4  4          5    11
5  5          3     1
6  6         14     9

#2


2  

This is actually a great use-case for the xmlEventParse function in the XML package. This is a 200+ MB file and the last thing you want to do is waste memory needlessly (XML parsing is notoriously memory intensive) and waste time going through nodes multiple times.

这实际上是XML包中的xmlEventParse函数的一个很好的用例。这是一个200+ MB的文件,您最不想做的事情就是不必要地浪费内存(XML解析是出了名的内存密集型),并浪费多次遍历节点的时间。

By using xmlEventParse you can also filter what you do or do not need and you can also get a progress bar snuck in there so you can see what's going on.

通过使用xmlEventParse,你也可以过滤你所做的或不需要的东西,你也可以得到一个进度条,这样你就可以看到发生了什么。

library(XML)
library(data.table)

# get the # of <rows> quickly; you can approximate if you don't know the
# number or can't run this and then chop down the size of the data.frame
# afterwards
system("grep -c '<row' ~/Desktop/p1.xml")
## 128010

n <- 128010

# pre-populate a data.frame
# you could also just write this data out to a file and read it back in
# which would negate the need to use global variables or pre-allocate
# a data.frame
dat <- data.frame(id=rep(NA_character_, n),
                  post_type_id=rep(NA_character_, n),
                  stringsAsFactors=FALSE)

# setup a progress bar since there are alot of nodes
pb <- txtProgressBar(min=0, max=n, style=3)

# this function will be called for each <row>
# again, you could write to a file/database/whatever vs do this
# data.frame population
idx <- 1
process_row <- function(node, tribs) {
  # update the progress bar
  setTxtProgressBar(pb, idx)
  # get our data (you can filter here)
  dat[idx, "id"] <<- tribs["Id"]
  dat[idx, "post_type_id"] <<- tribs["PostTypeId"]
  # update the index
  idx <<- idx + 1
}

# start the parser
info <- xmlEventParse("Posts.xml", list(row=process_row))

# close up the progress bar
close(pb)

head(dat)
##   id post_type_id
## 1  1            1
## 2  2            1
## 3  3            1
## 4  4            1
## 5  5            2
## 6  6            1

#1


2  

Using rvest (which is a wrapper around xml2) you can do it as follows:

使用rvest(它是xml2的包装),您可以按照以下方式进行:

require(rvest)
require(magrittr)
doc <- xml('<posts>
  <row Id="1" PostTypeId="1" 
AcceptedAnswerId="15" CreationDate="2010-07-19T19:12:12.510" Score="27" 
ViewCount="1647" Body="some text;" OwnerUserId="8" 
LastActivityDate="2010-09-15T21:08:26.077" 
Title="title" AnswerCount="5" CommentCount="1" FavoriteCount="17" />
</posts>')

rows <- doc %>% xml_nodes("row")
data.frame(
  Id = rows %>% xml_attr("id"),
  PostTypeId = rows %>% xml_attr("posttypeid")
)

Resulting in:

导致:

  Id PostTypeId
1  1          1

If you take Comments.xml
with

如果你把评论。xml与

data.frame(
  Id = rows %>% xml_attr("id"),
  PostTypeId = rows %>% xml_attr("postid"),
  score = rows %>% xml_attr("score")
)

You receive:

你收到:

> head(dat)
  Id PostTypeId score
1  1          3     5
2  2          5     0
3  3          9     0
4  4          5    11
5  5          3     1
6  6         14     9

#2


2  

This is actually a great use-case for the xmlEventParse function in the XML package. This is a 200+ MB file and the last thing you want to do is waste memory needlessly (XML parsing is notoriously memory intensive) and waste time going through nodes multiple times.

这实际上是XML包中的xmlEventParse函数的一个很好的用例。这是一个200+ MB的文件,您最不想做的事情就是不必要地浪费内存(XML解析是出了名的内存密集型),并浪费多次遍历节点的时间。

By using xmlEventParse you can also filter what you do or do not need and you can also get a progress bar snuck in there so you can see what's going on.

通过使用xmlEventParse,你也可以过滤你所做的或不需要的东西,你也可以得到一个进度条,这样你就可以看到发生了什么。

library(XML)
library(data.table)

# get the # of <rows> quickly; you can approximate if you don't know the
# number or can't run this and then chop down the size of the data.frame
# afterwards
system("grep -c '<row' ~/Desktop/p1.xml")
## 128010

n <- 128010

# pre-populate a data.frame
# you could also just write this data out to a file and read it back in
# which would negate the need to use global variables or pre-allocate
# a data.frame
dat <- data.frame(id=rep(NA_character_, n),
                  post_type_id=rep(NA_character_, n),
                  stringsAsFactors=FALSE)

# setup a progress bar since there are alot of nodes
pb <- txtProgressBar(min=0, max=n, style=3)

# this function will be called for each <row>
# again, you could write to a file/database/whatever vs do this
# data.frame population
idx <- 1
process_row <- function(node, tribs) {
  # update the progress bar
  setTxtProgressBar(pb, idx)
  # get our data (you can filter here)
  dat[idx, "id"] <<- tribs["Id"]
  dat[idx, "post_type_id"] <<- tribs["PostTypeId"]
  # update the index
  idx <<- idx + 1
}

# start the parser
info <- xmlEventParse("Posts.xml", list(row=process_row))

# close up the progress bar
close(pb)

head(dat)
##   id post_type_id
## 1  1            1
## 2  2            1
## 3  3            1
## 4  4            1
## 5  5            2
## 6  6            1