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01 Dealing with String Data

Dealing with String Data

How to use the KNIME Analytics Platform to identify and fix errors in String data.
Reading raw data file without separator
Converting & assigning appropriate column formats
Checking & correcting for invalid values
Extracting new columns from an existing column
Handling white space and case conversion
Changing the case of string columns
Extract eightcolumns
Cell Splitter By Position
Convert to Integer columns
String to Number
Remove whitespaces from beginning & end of string
String Manipulation (Multi Column)
Summary statistics
Statistics
Invalid Gender
Rule-based Row Filter
Drop unwanted columns
Column Filter
Extract Postalcode
String Manipulation
Gender count
Value Counter
Uppercase Gender
String Manipulation
Postalcode count
GroupBy
Gender count
Value Counter
Empty string to null Gender
String Manipulation
OrderDate conversion
String to Date&Time
ReadingCustomerOrders.txt
File Reader
CustomerOrders.table
Table Writer

Nodes

Extensions

Links

Download

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

Download Workflow
Created by: vijaykrishna.v
Created at: 2021-02-22
On NodePit since: 2024-12-16
Last update: 2025-11-09
Created with KNIME version: v5.8.0

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