The xmlconvert package is made to easily and comfortably
convert XML data to R dataframes and the other way around. It provides a
lot of options to control the conversion process and to export the
results to CSV or Excel files, if desired.
Just execute
install.packages("xmlconvert", dependencies = TRUE) in the
R console to install the package including all packages it depends on.
By default, the xlsx package for writing Excel files is not
installed together with xmlconvert. xmlconvert
will tell you when you need xlsx and will ask you to
install it then.
The functions xml_to_df() and df_to_xml()
are the two workhorses of the package.
The functions assume that each data record (e.g. a customer) in the XML data is stored in one XML element/tag; the individual fields (e.g. name, address, e-mail), however, can be represented in different ways.
An XML data file could like this:
<datarecord>
<field1>value1-1</field1>
<field2>value1-2</field2>
</datarecord>
<datarecord>
<field1>value2-1</field1>
<field2>value2-2</field2>
</datarecord>When working with the xml_to_df() and
df_to_xml() functions, we would first of all use the
records.tags argument to provide the tag name of the XML
element that represents the records, in this example
datarecord. Alternatively, the xml_to_df()’s
records.xpath argument can be used to supply an XPath
expression describing the location of the data records.
In the next step, we need to specify how to find the fields. In the
example above, each field within a data record has its own XML element,
and the tag name of this element is the field name. In this case, we
would use fields = "tags" to make it clear to the
xmlconvert functions that the fields are represented by XML
elements. Not always will the tag names be the field names. The XML
could also look like this:
<datarecord>
<field name="field1">value1-1</field>
<field name="field2">value1-2</field>
</datarecord>
<datarecord>
<field name="field1">value2-1</field>
<field name="field2">value2-2</field>
</datarecord>Here, the XML elements representing the fields all have the tag
field. The name of the field is not given by the tag name
but is an attribute (called name in our case) of the
field element. This attribute name can be supplied to the
xmlconvert functions using the fields.names
argument.
In this case, xml_to_df() could be called like this:
xml_to_df("mydata.xml", records.tag = "datarecord", fields = "tags", fields.names = "name")
However, instead of being XML elements, the data fields could also be represented by individual attributes, as in the following example:
<datarecord field1="value1-1" field2="value1-2" />
<datarecord field1="value2-1" field2="value2-2" />In this case, we use fields = "attributes" instead of
fields = "tags" to adjust to this XML data structure. Here,
a call of xml_to_df() could look like this:
xml_to_df("mydata.xml", records.tag = "datarecord", fields = "attributes")
The xmlconvert functions offer a lot of options to
specify which data fields are to be used, how to deal with missing
values, how to treat different data types and how to export the results.
Please consult the online help by executing ?xml_to_df in
the R console for more information on these options.
Joachim Zuckarelli
Twitter: [@jsugarelli](https://twitter.com/jsugarelli)