AUSTIN, Texas— WrangleWorks, a provider of tools for automating data work, has released its Wrangles Python package.
Wrangles dramatically reduces the knowledge and Python code needed to semantically cleanse and enrich data.
“Wrangles provides configurable transformations and recipes for data enrichment and automation,” said Chris Ince, CTO of WrangleWorks. “Conflicts are defined and executed using an intuitive, low-code configuration syntax that requires only the most basic knowledge of Python. With Wrangles, virtually anyone can automate the preparation and integration of data.
With Wrangles, citizen wranglers can:
- Extract meaningful information from unstructured text
- Quickly format and normalize data
- Classify data into categories and hierarchies using machine learning models Map and move data from one system to another
- Translate text accurately between languages
Wrangles was designed to deliver the clean, rich data required by modern analytical and e-commerce applications. It replaces manual data cleansing methods, which cannot keep pace with these large dynamic systems. Wrangles can be used freely by citizen wranglers to automate all facets of working with data, including applying application-specific semantics.
The Wrangles Python package is available at github and pypi.org.