Here are some thoughts, 🏵️🏵️👇

Grouping data by gender or age can help understand the different preferences and behaviors of different analysis.

Aggregating data involves summarizing the data to obtain a more concise and meaningful representation. For example, aggregating sales data by region or product can help identify the best-performing regions or products.

Data manipulation is an essential part of the data analysis process.
By understanding and following these steps, one can easily manipulate data to derive insights and solve complex problems.

Remember, engaging the services of a data scientist or data analyst can help you get the best insights from your data. ⏩⏩