I'm looking for a simple way of parsing complex text files into a pandas DataFrame. Below is a sample file, what I want the result to look like after parsing, and my current method.
I have also put this question on Stack Overflow. I eventually wrote a blog article to explain this to beginners. Sign up to join this community. The best answers are voted up and rise to the top. Home Questions Tags Users Unanswered. Parse complex text files using Python Ask Question. Asked 2 years, 3 months ago. Active 2 years, 3 months ago.
Viewed 36k times. Here is a sample file: Sample text A selection of students from Riverdale High and Hogwarts took part in a quiz. This is a record of their scores. DataFrame data data. Active Oldest Votes. Ash 4 4 bronze badges. Sign up or log in Sign up using Google.
Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information. You can do it without using regex. Return a pretty-printed version of the document. Whitespace within the pattern is ignored, except when in a character class or preceded by an unescaped backslashand, when a line contains a ' ' neither in a character class or preceded by an unescaped backslash, all characters from the leftmost such ' ' through the end of the line are ignored.
Learn more. How to parse a. Ask Question. Asked 3 years, 1 month ago. Active 3 years, 1 month ago. Viewed 3k times. Element 'root' root. SubElement root, 'filedata' celldata. SubElement celldata, title. ElementTree root tree. When a full program does not give expected resultsjust split it in smaller parts and try them separately. Here you should begin with simply parsing the input and print the parts you could find.
And only them try to build a XML file. Are they intentional? I tried the program, I am getting the XML structure and that too just the filedata tag. I took help of an answer to a SO question and changed the Regex according to my structure. I'll update the Regex which I used.
It only takes a minute to sign up. The problem is it takes too much time. Can you please look at the attached code and suggest ways to make it faster? The cause of the performance problem is that for every line where you encounter a new variable name, you open the same file again and scan through, looking at every line that contains the same variable name.
A root cause of your problem is that you aren't using data structures effectively. For example, you maintain a MyVariableList array, which you periodically sort so that you can do a binary search on it. What you want is a setor if you want to preserve the order of appearance of the variables in the output, an OrderedDict.
A reasonable approach would make just one pass through the file, accumulating statistics in a data structure as you go, and then write a summary of that data structure when you reach the end of the input. Even better, take the input from fileinput. Use the shell command to specify the input files and redirect the output to a file, and avoid hard-coding the input and output filenames in your script.
Then you could just write. Slicing each line using finds and splits all over the place is confusing.
How to Parse and Modify XML in Python?
You would be much better off trying to "make sense" of the input file fields, then using regular expression matches. Isn't that almost what you wanted? Of course there's a for in the END statement but it's a short one, it parses one key once. Turn this in pandas dataframe with this python script and you're done, you may have to use the pivot table feature in Pandas:. Sign up to join this community.
XML parsing in Python
The best answers are voted up and rise to the top. Home Questions Tags Users Unanswered. Asked 5 years ago. Active 4 years, 6 months ago.This article focuses on how one can parse a given XML file and extract some useful data out of it in a structured way. It was designed to store and transport data. It was designed to be both human- and machine-readable. The content of response now contains the XML file data which we save as topnewsfeed.
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We know that XML is an inherently hierarchical data format, and the most natural way to represent it is with a tree. Look at the image below for example:.
Here, we are using xml. ElementTree call it ET, in short module. Element Tree has two classes for this purpose — ElementTree represents the whole XML document as a tree, and Element represents a single node in this tree.
Interactions with a single XML element and its sub-elements are done on the Element level. Here, we create an ElementTree object by parsing the passed xmlfile. Now, once you have taken a look at the structure of your XML file, you will notice that we are interested only in item element.
You can read more about supported XPath syntax here. Now, we know that we are iterating through item elements where each item element contains one news. So, we create an empty news dictionary in which we will store all data available about news item. To iterate though each child element of an element, we simply iterate through it, like this:. Now, notice a sample item element here:. We will have to handle namespace tags separately as they get expanded to their original value, when parsed.
So, we do something like this:. Here, we are interested in url attribute of media:content namespace tag. Now, for all other children, we simply do:. So, finally, a sample item element is converted to a dictionary and looks like this:. Then, we simply append this dict element to the list newsitems. Finally, this list is returned. To know more about writing dictionary elements to a CSV file, go through this article: Working with CSV files in Python So now, here is how our formatted data looks like now:.
As you can see, the hierarchical XML file data has been converted to a simple CSV file so that all news stories are stored in form of a table. This makes it easier to extend the database too. Also, one can use the JSON-like data directly in their applications! This is the best alternative for extracting data from websites which do not provide a public API but provide some RSS feeds.
All the code and files used in above article can be found here. This article is contributed by Nikhil Kumar.XML, or Extensible Markup Language, is a markup-language that is commonly used to structure, store, and transfer data between systems. With Python being a popular language for the web and data analysis, it's likely you'll need to read or write XML data at some point, in which case you're in luck.
Throughout this article we'll primarily take a look at the ElementTree module for reading, writing, and modifying XML data. We'll also compare it with the older minidom module in the first few sections so you can get a good comparison of the two.
The DOM is an application programming interface that treats XML as a tree structure, where each node in the tree is an object. Thus, the use of this module requires that we are familiar with its functionality.
It is also likely a better candidate to be used by more novice programmers due to its simple interface, which you'll see throughout this article. In this article, the ElementTree module will be used in all examples, whereas minidom will also be demonstrated, but only for counting and reading XML documents. In the examples below, we will be using the following XML file, which we will save as "items.
As you can see, it's a fairly simple XML example, only containing a few nested objects and one attribute. However, it should be enough to demonstrate all of the XML operations in this article. In order to parse an XML document using minidomwe must first import it from the xml. The parse function has the following syntax:. Here the file name can be a string containing the file path or a file-type object.
The function returns a document, which can be handled as an XML type. Thus, we can use the function getElementByTagName to find a specific tag. Since each node can be treated as an object, we can access the attributes and text of an element using the properties of the object. In the example below, we have accessed the attributes and text of a specific node, and of all nodes together. If we wanted to use an already-opened file, can just pass our file object to parse like so:. Also, if the XML data was already loaded as a string then we could have used the parseString function instead.
ElementTree presents us with an very simple way to process XML files. As always, in order to use it we must first import the module. In our code we use the import command with the as keyword, which allows us to use a simplified name ET in this case for the module in the code.
Following the import, we create a tree structure with the parse function, and we obtain its root element. Once we have access to the root node we can easily traverse around the tree, because a tree is a connected graph. Using ElementTreeand like the previous code example, we obtain the node attributes and text using the objects related to each node.
As you can see, this is very similar to the minidom example. One of the main differences is that the attrib object is simply a dictionary object, which makes it a bit more compatible with other Python code. We also don't need to use value to access the item's attribute value like we did before. You may have noticed how accessing objects and attributes with ElementTree is a bit more Pythonic, as we mentioned before.
This is because the XML data is parsed as simple lists and dictionaries, unlike with minidom where the items are parsed as custom xml. Attr and "DOM Text nodes". As in the previous case, the minidom must be imported from the dom module. This module provides the function getElementsByTagNamewhich we'll use to find the tag item.We often require to parse data written in different languages.
Python provides numerous libraries to parse or split data written in other languages. What is XML?
ElementTree Module. XML is exclusively designed to send and receive data back and forth between clients and servers. Take a look at the following example:.
Python allows parsing these XML documents using two modules namely, the xml. Parsing means to read information from a file and split it into pieces by identifying parts of that particular XML file.
This module helps us format XML data in a tree structure which is the most natural representation of hierarchical data. Element type allows storage of hierarchical data structures in memory and has the following properties:. ElementTree is a class that wraps the element structure and allows conversion to and from XML.
Let us now try to parse the above XML file using python module. The first is by using the parse function and the second is fromstring function. The parse function parses XML document which is supplied as a file whereas, fromstring parses XML when supplied as a string i.
As mentioned earlier, this function takes XML in file format to parse it. As you can see, The first thing you will need to do is to import the xml. ElementTree module. When you execute the above code, you will not see outputs returned but there will be no errors indicating that the code has executed successfully.
To check for the root element, you can simply use the print statement as follows:. You can also use fromstring function to parse your string data. In case you want to do this, pass your XML as a string within triple quotes as follows:. The above code will return the same output as the previous one.The xml. Changed in version 3.
ElementTree module is not secure against maliciously constructed data. If you need to parse untrusted or unauthenticated data see XML vulnerabilities.
Parsing text with Python
This is a short tutorial for using xml. ElementTree ET in short. The goal is to demonstrate some of the building blocks and basic concepts of the module.
XML is an inherently hierarchical data format, and the most natural way to represent it is with a tree. ET has two classes for this purpose - ElementTree represents the whole XML document as a tree, and Element represents a single node in this tree.
Interactions with a single XML element and its sub-elements are done on the Element level. Other parsing functions may create an ElementTree. Check the documentation to be sure. As an Elementroot has a tag and a dictionary of attributes:. Not all elements of the XML input will end up as elements of the parsed tree. Currently, this module skips over any XML comments, processing instructions, and document type declarations in the input.Python Tutorial: File Objects - Reading and Writing to Files
Most parsing functions provided by this module require the whole document to be read at once before returning any result. It is possible to use an XMLParser and feed data into it incrementally, but it is a push API that calls methods on a callback target, which is too low-level and inconvenient for most needs.
Sometimes what the user really wants is to be able to parse XML incrementally, without blocking operations, while enjoying the convenience of fully constructed Element objects. Here is an example:. The obvious use case is applications that operate in a non-blocking fashion where the XML data is being received from a socket or read incrementally from some storage device.
In such cases, blocking reads are unacceptable. Element has some useful methods that help iterate recursively over all the sub-tree below it its children, their children, and so on. For example, Element. More sophisticated specification of which elements to look for is possible by using XPath.
ElementTree provides a simple way to build XML documents and write them to files. The ElementTree.
Once created, an Element object may be manipulated by directly changing its fields such as Element. We can remove elements using Element. The SubElement function also provides a convenient way to create new sub-elements for a given element:. Also, if there is a default namespacethat full URI gets prepended to all of the non-prefixed tags.