5/25/2023 0 Comments Raw data aob extractorHe may then clean up the character values in the dataset as well to end up with the following “clean” data: The scout may decide to remove the last row entirely since it has multiple missing values. This dataset represents the raw data because it’s collected directly by the scout and it hasn’t been cleaned or processed in any way.īefore using this data to create summary tables, charts, or anything else, the scout would first remove any missing values and clean up any “dirty” data values.įor example, we can spot several values in the dataset that need to be transformed or removed: Imagine that a basketball scout collects the following raw data for 10 players on a professional basketball team: For example, raw data might be collected for various statistics for professional basketball players. One field in which raw data is often collected is sports. The following example illustrates how raw data might be collected and used in real life. The whole point of gathering raw data is to eventually use it to gain a better understanding of some phenomena or use it to build some type of predictive model. Once this data has been gathered, it can then be cleaned, transformed, summarized, and visualized. In any type of data analysis project, the first step is gathering raw data. In statistics, raw data refers to data that has been collected directly from a primary source and has not been processed in any way.
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