WrangleWorks Announces Wrangles Python Package is Now Open Source
Wrangles dramatically reduces the Python knowledge and code required to clean and semantically enrich data.
Automate data work with Wrangles Python package
Wrangles provides configurable transformations and recipes for data enrichment and automation. With Wrangles, virtually anyone can automate data preparation and integration.”
AUSTIN, TEXAS, UNITED STATES, September 20, 2022 /EINPresswire.com/ -- WrangleWorks, provider of tools to automate data work, has open- sourced its Wrangles Python package. Wrangles dramatically reduces the Python knowledge and code required to clean and semantically enrich data.— Chris Ince, WrangleWorks CTO
“Wrangles provides configurable transformations and recipes for data enrichment and automation,” said Chris Ince, WrangleWorks CTO. “Wrangles are defined and run using an intuitive, low-code configuration syntax that requires only the most basic knowledge of Python. With Wrangles, virtually anyone can automate data preparation and integration.”
With Wrangles, “citizen wranglers” can:
* Extract meaningful information from unstructured text
* Format and standardize data quickly
* 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 built to provide the clean, enriched data required by modern analytical and ecommerce applications. It replaces manual data cleaning methods, which cannot keep pace with such large, dynamic systems. Wrangles can be used freely by citizen wranglers to automate all facets of data work, including applying application-specific semantics.
The Wrangles Python package is available on github and pypi.org.
About WrangleWorks
WrangleWorks helps companies feed meaningful data to analytical applications. Wrangles simplify aligning data structures and semantics for integrating ecommerce, pricing and product information management (PIM) systems. The Wrangles platform enables companies to automate data work, transforming data-dependent processes while dramatically reducing costs and cycle times.
Eric Hills
WrangleWorks
eric@wrangleworks.com
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