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Data manipulation refers to the process of transforming raw data into a format that is more suitable for analysis and modeling. The goal of data manipulation is to clean, organize, and transform data into a usable form that can be easily consumed and analyzed. It involves a range of techniques and methods used to preprocess and organize data, making it easier to work with and analyze. This section will provide an overview of the key techniques involved in data manipulation, including indexing, slicing, filtering, and sorting. It is an important part of any data analysis or data science project due to several reasons:
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