Which Python library provides tools for working with structured data and is often used in data analysis tasks, especially in financial data?

Seaborn
PySpark
Scikit-learn
Seaborn

The correct answer is C. Scikit-learn.

Scikit-learn is a free and open-source machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

Scikit-learn is often used in data analysis tasks, especially in financial data. It provides a wide range of tools for working with structured data, including data loading, cleaning, and preprocessing. It also includes a number of machine learning algorithms that can be used to train models on structured data.

Seaborn is a Python data visualization library based on Matplotlib. It provides a high-level interface for drawing attractive statistical graphics. Seaborn is built on top of Matplotlib, but provides a number of features that make it easier to use for data visualization. These features include a variety of statistical plots, a grammar of graphics, and a number of helpful tools for data exploration.

PySpark is an open-source distributed processing framework for large-scale data processing. It is built on top of Apache Spark and provides a high-level API for working with structured and unstructured data. PySpark is often used in data analysis tasks, especially in big data applications.

In conclusion, the correct answer is C. Scikit-learn. Scikit-learn is a Python library that provides tools for working with structured data and is often used in data analysis tasks, especially in financial data.