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Data Wrangling (also known as Data Munging) is the process of transforming data from its original “raw” form into a more digestible format and organizing sets from various sources into a singular coherent whole for further processing. | Data Wrangling (also known as Data Munging) is the process of transforming data from its original “raw” form into a more digestible format and organizing sets from various sources into a singular coherent whole for further processing. | ||
==Sources== | |||
[http://www.datascienceglossary.org Source : Datascience glossary] | [http://www.datascienceglossary.org Source : Datascience glossary] | ||
[https://theappsolutions.com/blog/development/data-wrangling-guide-to-data-preparation Theappsolution.com] | |||
Dernière version du 29 janvier 2024 à 12:22
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Also, data munging. The conversion of data, often through the use of scripting languages, to make it easier to work with. If you have 900,000 birthYear values of the format yyyy-mm-dd and 100,000 of the format mm/dd/yyyy and you write a Perl script to convert the latter to look like the former so that you can use them all together, you're doing data wrangling. Discussions of data science often bemoan the high percentage of time that practitioners must spend doing data wrangling; the discussions then recommend the hiring of data engineers to address this. See also Perl, Python, shell, data engineer
Data Wrangling (also known as Data Munging) is the process of transforming data from its original “raw” form into a more digestible format and organizing sets from various sources into a singular coherent whole for further processing.
Sources
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