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replace_special_characters

Call or Deploy replace_special_characters ?

✅ You can call this replace_special_characters bigfunction directly from your Google Cloud Project (no install required).

  • This replace_special_characters function is deployed in bigfunctions GCP project in 39 datasets for all of the 39 BigQuery regions. You need to use the dataset in the same region as your datasets (otherwise you may have a function not found error).
  • Function is public, so it can be called by anyone. Just copy / paste examples below in your BigQuery console. It just works!
  • You may prefer to deploy the BigFunction in your own project if you want to build and manage your own catalog of functions. This is particularly useful if you want to create private functions (for example calling your internal APIs). Discover the framework

Public BigFunctions Datasets:

Region Dataset
eu bigfunctions.eu
us bigfunctions.us
europe-west1 bigfunctions.europe_west1
asia-east1 bigfunctions.asia_east1
... ...

Description

Signature

replace_special_characters(string, replacement)

Description

Replace most common special characters in a string with replacement

Examples

select bigfunctions.eu.replace_special_characters('%♥!Hello!*♥#', '')
select bigfunctions.us.replace_special_characters('%♥!Hello!*♥#', '')
select bigfunctions.europe_west1.replace_special_characters('%♥!Hello!*♥#', '')
+----------------+
| cleaned_string |
+----------------+
| Hello          |
+----------------+

Need help using replace_special_characters?

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For professional suppport, don't hesitate to chat with us.

Found a bug using replace_special_characters?

If the function does not work as expected, please

  • report a bug so that it can be improved.
  • or open the discussion with the community on Slack.

For professional suppport, don't hesitate to chat with us.

Use cases

A use case for the replace_special_characters function is cleaning user-generated data before storing or processing it. Imagine you have a website where users can submit product reviews. These reviews might contain special characters like emoticons, punctuation marks beyond the standard set, or even unintended HTML entities. These characters can cause problems when:

  • Storing data in a database: Some databases may not handle certain special characters correctly, leading to errors or data corruption.
  • Displaying data: Special characters may not render correctly on different browsers or devices, leading to a poor user experience.
  • Performing text analysis: Special characters can interfere with natural language processing tasks like sentiment analysis or topic modeling.

Using the replace_special_characters function, you could clean the user-submitted reviews before storing them in your database. For example:

SELECT bigfunctions.us.replace_special_characters(review_text, ' ') AS cleaned_review
FROM `your_project.your_dataset.user_reviews`;

This query would replace all special characters in the review_text column with spaces, resulting in a cleaner version of the review text that is more suitable for storage, display, and analysis. This helps to ensure data consistency and improve the performance of downstream tasks.

Here's another example, focusing on creating URL-friendly strings (slugs):

SELECT bigfunctions.us.replace_special_characters('This is a product title with special characters!@#$%^&*()', '-') AS url_slug

This would output This-is-a-product-title-with-special-characters-------, which, after removing repeating hyphens, could be used as a URL slug.

In essence, the replace_special_characters BigQuery function assists in data sanitization and preparation for various uses by removing or replacing characters that could otherwise cause issues.

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