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Python has several libraries that are widely used by data scientists:
1. **NumPy**: For numerical computations and handling large arrays.
2. **Pandas**: For data manipulation and analysis.
3. **Matplotlib**: For creating static, animated, and interactive visualizations.
4. **Seaborn**: For statistical data visualization.
5. **Scikit-learn**: For machine learning algorithms and data preprocessing.
6. **TensorFlow/PyTorch**: For deep learning models.
7. **SciPy**: For scientific and technical computing.
8. **NLTK/Spacy**: For natural language processing.
These libraries help data scientists efficiently analyze and visualize data, build models, and make predictions.
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Python libraries for data science:
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