XML to CSV
Extract data from XML to CSV in your browser, no installation needed.
.pdf · up to 2 GB
What it's for
XML to CSV for data analysis
Compatible with everything
Resulting CSV importable in Excel, Google Sheets, pandas, R, Power BI or any data tool.
100% private
Your XML (which may contain confidential business data) is processed only in your browser.
Smart extraction
Automatically detects rows, flattens nested structures with dot notation, concatenates arrays.
Instant
Real-time conversion without uploading files to any server. No signup, no limits.
How it works
Three steps, no hassle
Paste your XML
Paste the XML content: it can be a SOAP response, RSS feed, configuration file, or any XML with repeated data.
Automatic row detection
The tool detects repeated sibling elements (the level representing rows) and extracts all fields as CSV columns.
Download the CSV
Copy or download the resulting CSV. Compatible with Excel, Google Sheets, pandas, and any data analysis tool.
FAQ
Got questions?
The tool analyzes the XML and looks for the level of repeated sibling elements: if there are multiple <product>, <item>, <record>, or similar elements at the same level, they are treated as rows. The algorithm identifies the element that appears most often as the row candidate. For example, in an inventory XML with <inventory><products><product>...</product><product>...</product></products></inventory>, the <product> elements are the rows. Fields within each <product> become CSV columns. XML attributes are also included as columns.
CSV columns are derived from the union of all fields found across all row elements. If the first <product> has fields id, name and price, but the second also has stock, the CSV will include all four columns (id, name, price, stock) and cells without a value for that element are left empty. This ensures no field is lost even if not all elements have the same fields, which is common in real-world XML where some fields are optional.
For child elements of rows that are simple nested objects, the tool uses dot notation to flatten the structure: <address><city>Madrid</city></address> becomes the column address.city with value Madrid. For sub-arrays (multiple elements of the same type within a row), they are concatenated with a separator (;) in a single column: <tags><tag>A</tag><tag>B</tag></tags> becomes tags = A;B. This maximizes the information preserved in a tabular format.
The CSV standard (RFC 4180) requires that fields containing commas, double quotes, or line breaks be wrapped in double quotes. Double quotes within the value are escaped by doubling them (""). This tool follows the RFC 4180 standard to ensure the resulting CSV is correctly importable in Excel, Google Sheets, and any CSV parser. Values with commas (common in XML data that may contain lists) and values with line breaks (common in description fields) are handled correctly.
XML to CSV is especially useful for: 1) SOAP responses: SOAP services (very common in banking systems, ERP, and legacy systems) return XML. Converting to CSV facilitates analysis in Excel or importing into databases. 2) RSS/Atom feeds: converting RSS feed articles to CSV for content analysis or media monitoring. 3) Configuration exports: many enterprise systems (SAP, Oracle, Salesforce) export data in XML. 4) ETL workflows: in data pipelines, XML to CSV is a common transformation step before loading to a data warehouse.
XML in the enterprise: SOAP, RSS and SVG, data migration, and ETL workflows
XML (eXtensible Markup Language) was published by the W3C in 1998 and during the 2000s became the standard format for data exchange. SOAP (Simple Object Access Protocol), based on XML, dominated web service architectures until the arrival of REST. Today, a large number of enterprise legacy systems still use SOAP and XML: SAP, Oracle ERP, SWIFT banking systems, HL7 and FHIR healthcare standards, and many government systems. Although REST and JSON have replaced XML in modern development, XML remains ubiquitous in enterprise systems integration.
RSS (Really Simple Syndication) and Atom are XML formats for web content feeds. Although RSS feeds seem like a technology of the past, they remain widely used by podcasts (iTunes/Apple Podcasts uses RSS for distribution), blogs, news portals, and media monitoring tools. SVG (Scalable Vector Graphics) is also XML and is integrated into HTML5. XML is also the base format for XLSX (Excel), DOCX (Word), and PPTX (PowerPoint): these files are ZIP archives containing XML internally.
In ETL (Extract, Transform, Load) workflows in data engineering, XML to CSV is a very common transformation. Apache NiFi, Apache Airflow, dbt, and other ETL tools support XML transformations. In Python, the lxml and xml.etree.ElementTree libraries are the standard XML parsers, and pandas can read XML directly with pd.read_xml(). In the context of data migration, many legacy systems only export in XML, and conversion to CSV is the first step for importing data into modern systems like PostgreSQL, BigQuery, or Snowflake.