What are the common techniques used in data manipulation?

Data manipulation involves the process of altering, transforming, or modifying data to extract meaningful insights or prepare it for analysis. There are several common techniques used in data manipulation. Firstly, filtering is a technique that involves selecting specific data based on certain criteria or conditions. This helps in narrowing down the dataset to focus on relevant information. Secondly, sorting arranges the data in a specific order, such as ascending or descending, based on one or multiple variables. This aids in organizing the data for easier analysis. Thirdly, merging or joining combines multiple datasets into one, enhancing the ability to analyze relationships and correlations. Another common technique is aggregating, where data is grouped together and summarized using functions like sum, average, count, etc. This helps in understanding patterns and trends in the data. Additionally, data manipulation often includes techniques like transforming variables, cleaning or imputing missing values, and creating new derived variables. These techniques collectively enable analysts to effectively manipulate data for various purposes, such as reporting, visualization, and predictive modeling.

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