mulesoft/data-weave-analytics-library

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DataWeave Analytics Library The DataWeave Analytics library provides a collection of simple functions intended to perform data analysis over datasets. DataWeave, which supports data transformations in multiple formats, is a fast analyzer for datasets. This library fills a gap in some commonly used functionalities. Overview The CSVSummary on analytics::summaries consumes a CSV file and produces a summary of the values on the different columns present in it. For example, assume the following CSV input: id,time,age 1,234,18 2,333,24 3,108,15 4,444,44 The CSVSummary mapping produces the following JSON output from the CSV input: { "id": { "mean": 2.5, "modes": [ "1", "2", "3", "4" ], "median": 2.5, "stdev": 1.118033988749894848204586834365638, "quartiles": [ 1.5, 2.5, 3.5 ] }, "time": { "mean": 279.75, "modes": [ "234", "333", "108", "444" ], "median": 283.5, "stdev": 123.8999092009352523399554085511010, "quartiles": [ 171, 283.5, 388.5 ] }, "age": { "mean": 25.25, "modes": [ "18", "24", "15", "44" ], "median": 21, "stdev": 11.29988937998952271159312403049506, "quartiles": [ 16.5, 21, 34 ] } } Notice that the result provides a summary consisting of the mean, the modes, the median, the standard deviation, and the quartiles of the values of each column in the CSV file. Contributions Welcome Contributions to this project can be made through Pull Requests and Issues on the GitHub Repository. Before creating a pull request review the following: LICENSE SECURITY CODE_OF_CONDUCT When you submit your pull request, you are asked to sign a contributor license agreement (CLA) if we don't have one on file for you.