Which Python library is commonly used for data profiling and generating summary statistics for datasets?

The correct answer is D. pandas-profiling.

pandas-profiling is a Python library that provides a high-level interface for data profiling and generating summary statistics for datasets. It is built on top of pandas, a popular Python library for data analysis.

pandas-profiling provides a number of features that make it well-suited for data profiling, including:

• A graphical interface that allows users to explore their data and identify potential issues.
• A variety of summary statistics that can be generated for each column in a dataset.
• The ability to generate reports that can be shared with others.

pandas-profiling is a valuable tool for anyone who needs to analyze and understand their data. It is easy to use and provides a wealth of information about a dataset.

Here is a brief explanation of each option:

• A. Statsmodels is a Python library that provides a variety of statistical modeling tools. It is not commonly used for data profiling.
• B. Seaborn is a Python library that provides a variety of visualization tools. It is not commonly used for data profiling.
• C. Pandas is a Python library that provides a variety of data analysis tools. It can be used for data profiling, but pandas-profiling is a more specialized library that is better suited for this task.