CSV, JSON, or XML: How to Choose Data Formats for Analysis

csv vs xml

It could make the difference between an ok app or a great app. CSV, JSON, and XML are three of the most common formats for storing and transferring data. Each of these formats has its own unique properties that make them well suited for different types of use cases. Microsoft Excel is the most widely used spreadsheet application for opening and editing CSV files, however tools like Numbers for Mac or Google Sheets are also common.

Convert XML to CSV Like a Pro – Essential Tools & Methods

For example, in an XML file representing a bookstore, you can have nested elements like , , and . Online converters provide quick, hassle-free conversion without needing to install software. They’re ideal for real-time tasks, offering easy schema validation, different file formats interoperability, csv vs xml and immediate data export. Convenience and accessibility make these tools invaluable for data integration and migration tasks. An XML to CSV converter reads XML files, parses their hierarchical structure, extracts data embedded within XML tags, and maps this data into a CSV format.

csv vs xml

more stack exchange communities

While JSON’s primary purpose lies in facilitating data transmission between web servers and web applications, its versatility allows it to be employed in various programming scenarios. An XML to CSV converter transforms XML data into CSV format, enabling data manipulation in tools like Excel. These converters often parse XML tags, extracting structured data and reformatting it into rows and columns, aligning with CSV’s tabular structure. XML (eXtensible Markup Language) stands for structure and flexibility in data storage. It’s a versatile format allowing users to define their own tags, making it perfect for various applications, particularly where data serialization and data exchange are involved. CSV files are simple and supported by many applications, including spreadsheets and database management systems.

What is the difference between the CSV and XML export formats?

For those familiar with indentations in Python, YAML is a walk in the park. Before that, let’s take a quick look at what these formats are. We’ve decided to provide XML and JSON due to the difficulty in recursion in CSV needing multiple calls for a single logical operation. JSON doesn’t have a parser in Qt and Protocol Buffers doesn’t seem to have a non-alpha PHP implementation so they are out for the moment too but will probably be supported eventually. For a full list of common refer to the data sheet of Flexter, our enterprise XML converter.

XML in SOAP provides data typing and validation through XML schemas. This approach provides robust error handling and advanced security features as well and is ideal for highly reliable and secure applications. A well-known example is the Twitter (now X) API, which transmits data, such as tweets, between its servers and third-party apps in JSON format. If you’ve ever tweeted something, you were using JSON and didn’t even know it. Each tweet is contained in a JSON object with the tweet’s content, user details, hashtags, and so on. This structure enables you to access and parse the tweet’s data, allowing tweet integration into your apps seamlessly.

  • It focuses on storing and organizing data without concerning itself with the visual representation.
  • Its text-based nature makes it easily readable and writable for humans.
  • You may never have heard of XML before, but you’re probably familiar (if only in passing) with it’s cousin, HTML.
  • On the other hand, CSV files are simple text-based files that store tabular data.
  • Spreadsheet applications, such as Microsoft Excel, convert CSV files into a tabular format, with each row representing a record and each column representing a field.

You can open a CSV file without Excel, by using a text editor. However, the contents won’t be formatted in columns, as when viewed from a spreadsheet. That being said, in many cases, you would find that many other symbols are used as delimiters such as space, tab, or hyphen. It’s easy to read and write by humans, and easy to interpret by computers.

Despite the drawbacks, CSV files are used extensively in the business domain. It helps the organizations move and export a large amount of data to a more concentrated database. The need to convert between types of data has become very common, a fact that we can also certify through Google Trends. We can obtain proof of this by analyzing the volume of demand for the three formats (XML, CSV, and JSON) over several years, through Google Trends. As mentioned, its verbose structure can create additional overhead compared to the more efficient JSON format. If I haven’t provided enough clarity yet, these FAQs dive deeper into the key differences and unique benefits these formats offer.

In these cases, you might need to use a technique called normalization to transform XML to CSV. This breaks down the XML file into several CSV files connected by a foreign key. For a thorough explanation of these processes, check out our other resource, “Convert XML to CSV Like a Pro”. As I’ve mentioned, XML data format can represent complex data structures. Because JSON has no predefined schema, it’s ideal for document-based NoSQL databases, like MongoDB, Firebase, and CouchDB, that are designed for dynamic and evolving data models. This flexibility is useful for applications like social media platforms where user-generated content like posts and comments require adaptability.

Sure, there’s a semi-standard way to do escaping in CSV (i.e., “the way Excel does it”), and it’s not exactly hard to write yourself, but it does take some time. And then you’ve got to implicitly agree on a character encoding out-of-band. But then, because it’s so simple, people try to write it themselves, and invariably screw up either #2 or #3. Structured, human readable, easier to edit, validation, parsability, transformability, typing, namespaces, powerful libraries behind it, are all amongst many of the reasons.

Though no longer the go-to, XML is still the first choice for some popular applications today. ACORD is their standard for data exchange and uses XML to standardize data exchange between systems and stakeholders. What XML brings to the insurance game is interoperability between new and existing applications through consistent data formatting and validation. Finance people aren’t always tech people, so developers rely on CSV data files, which allows them to export data to and from their app using intuitive, (easy to use), no-code tools.