Gemini in Google Sheets just became your coworker who actually loves Excel
Google has announced new smart features for Gemini in Google Sheets aimed at simplifying data analysis and visualization for users.
Gemini can now do more complex data analysis in Google Sheets
If you love nothing more than good data visualization, Google’s latest Sheets update will be right up your alley. The company has begun rolling out an upgrade to the app’s Gemini side panel, a feature it introduced this past summer,
Gemini in Google Sheets Gets Updated With Data Analysis and Visualising Tools
Gemini in Google Sheets is getting a major upgrade that will allow the artificial intelligence (AI) tool to analyse and visualise user data. Announced on Wednesday, the new features are currently being rolled out to the Google Workspace subscribers and those subscribed to the Google One AI Premium plan.
Gemini in Google Sheets will write Python code to generate insights, charts
The Gemini side panel in Google Sheets is being updated to let you more easily visualize and analyze data through insights and charts.
Gemini AI Just Made Google Sheets a Chart Creating Powerhouse
New AI functions to "perform actions or answer questions to address a wide variety of scenarios" added to Google Sheets.
Google just gave Gemini the babelfish treatment in Docs, Drive, Gmail, and Sheets
Google has expanded Gemini's image generation in Workspace to seven more languages. The feature is now available in Docs, Sheets, Drive, and Gmail but not yet in Slides. Google One AI Premium users also get access,
Gemini can now generate charts and visualize data in Google Sheets
You can use the charts generated by Gemini as static images over cells in your spreadsheet. Google notes that your data should be in a consistent format with clear headers and no missing values to get the most accurate results. You need to be as specific as possible so the chatbot can understand your query.
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Gemini AI can automatically turn your spreadsheets into charts
Google says Gemini does all of this by creating and running Python code, then producing an analysis of the code’s results.