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How to Clean String Data

Cleaning text and string data involves systematically removing unwanted characters, correcting formatting issues, and standardizing text. This process ensures that textual information is consistent, readable, and ready for further analysis or reporting.

Data basics how-toData Transformation
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Workflow
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How to Clean String Data

How This Workflow Works

This workflow demonstrates a straightforward approach to cleaning text data by applying a series of transformations that remove unwanted characters, whitespaces or symbols, adjust formatting, and standardize the content. It then allows you to compare the original and cleaned text side-by-side to verify the results.

Key Features:

  • Remove unwanted characters and symbols from text
  • Automatically handle accents and non-ASCII characters
  • Standardize text casing, formatting and link hyperlinks
  • Easily compare original vs. cleaned text to check results

Step-by-step:

1. Apply Text Cleaning Operations:

The workflow processes each text entry to remove accents, non-ASCII characters, symbols, and trailing spaces. It also standardizes the casing, ensuring that the text is uniform and ready for reliable comparison and matching.

2. Format and Enhance Cleaned Text:

After cleaning, the text is further formatted for readability. This includes wrapping lines for better display and converting any detected hyperlinks into clickable links, making the data easier to review and use.

3. Visualize and Compare Results:

The cleaned and original text are displayed side-by-side in a table view. This allows you to quickly verify that the cleaning steps have worked as intended and to spot any remaining inconsistencies.

How to Get Started