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Automatic_​Cleaning

Automatic Cleaning Workflow
If there are no columns with "id" in the name, this path will not run. If the dataset does not have multiple date / datetime columns, this path will beblocked, which is normal. Node 456Node 509Node 510Node 514Node 515Node 516 File Reader Outlier Detection Binary valuecolumns detecter Numerical ColumnsExploration Outlier Detection Strings Exploration Missing ValueColumn Splitter Calculate the duration of alldates from the reference Convert IDinto Strings Constant&MissingColumns Splitter Date Format names ofconstant columns names of missingcolumns names of columnswith 15%-50% missing names of columnswith 50%-90% missing names of columns with90%-100% missing If there are no columns with "id" in the name, this path will not run. If the dataset does not have multiple date / datetime columns, this path will beblocked, which is normal. Node 456Node 509Node 510Node 514Node 515Node 516 File Reader Outlier Detection Binary valuecolumns detecter Numerical ColumnsExploration Outlier Detection Strings Exploration Missing ValueColumn Splitter Calculate the duration of alldates from the reference Convert IDinto Strings Constant&MissingColumns Splitter Date Format names ofconstant columns names of missingcolumns names of columnswith 15%-50% missing names of columnswith 50%-90% missing names of columns with90%-100% missing

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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Created by: ahallock
Created at: 2020-09-25
On NodePit since: 2022-01-12
Last update: 2024-04-28
Created with KNIME version: v4.3.0
Tags: data cleaningEDA

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