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  2. Help:Conditional tables - Wikipedia

    en.wikipedia.org/wiki/Help:Conditional_tables

    However, sources and notes referred to in the muted cells won't get suppressed with the other contents, to the effect that they continue to be listed at the end of an article without any references to them occurring in the article's text.

  3. Google Docs - Wikipedia

    en.wikipedia.org/wiki/Google_Docs

    Google Docs is an online word processor and part of the free, web-based Google Docs Editors suite offered by Google. Google Docs is accessible via a web browser as a web-based application and is also available as a mobile app on Android and iOS and as a desktop application on Google's ChromeOS .

  4. Module:Table empty cell/doc - Wikipedia

    en.wikipedia.org/wiki/Module:Table_empty_cell/doc

    Module:Table empty cell is used to create an empty table cell with alt and title texts. Parameter list. Parameter Explanation Status alt_text; 1;

  5. AOL Mail Help - AOL Help

    help.aol.com/products/new-aol-mail

    You've Got Mail!® Millions of people around the world use AOL Mail, and there are times you'll have questions about using it or want to learn more about its features. That's why AOL Mail Help is here with articles, FAQs, tutorials, our AOL virtual chat assistant and live agent support options to get your questions answered.

  6. Comma-separated values - Wikipedia

    en.wikipedia.org/wiki/Comma-separated_values

    Comma-separated values (CSV) is a text file format that uses commas to separate values, and newlines to separate records. A CSV file stores tabular data (numbers and text) in plain text, where each line of the file typically represents one data record.

  7. AOL Mail

    mail.aol.com

    Get AOL Mail for FREE! Manage your email like never before with travel, photo & document views. Personalize your inbox with themes & tabs. You've Got Mail!

  8. AOL latest headlines, entertainment, sports, articles for business, health and world news.

  9. Data cleansing - Wikipedia

    en.wikipedia.org/wiki/Data_cleansing

    Data cleansing or data cleaning is the process of identifying and correcting (or removing) corrupt, inaccurate, or irrelevant records from a dataset, table, or database.It involves detecting incomplete, incorrect, or inaccurate parts of the data and then replacing, modifying, or deleting the affected data. [1]