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3. **Perhatikan Pola Kalimat:** Perhatikan pola kalimat *active voice* dan *passive voice*. Dengan memahami polanya, kalian akan lebih mudah mengubah kalimat dari satu bentuk ke bentuk yang lain.
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The choice between **Pandas** and **Spark** often depends on the level of experience and the project's requirements. For data scientists who are new to data analysis or work with smaller datasets, **Pandas** is a great starting point. It allows you to quickly prototype solutions, explore data, and build models. For experienced data scientists who need to handle large datasets or require real-time processing, **Spark** is a more suitable choice. While the initial setup may be more complex, Spark's scalability and performance advantages make it a worthwhile investment. Some data scientists are also bridging the gap by using libraries like Koalas, which provide a Pandas-like interface on top of Spark, allowing you to use familiar syntax with the scalability of Spark.
