The correct answer is D. pyarrow.
pyarrow is a Python library that provides a unified interface for reading and writing data in a variety of formats, including Apache Parquet. It is designed to be efficient and scalable, and
it supports a wide range of features, such as schema evolution and partitioning.Matplotlib is a Python library for plotting data. It is widely used for scientific and engineering applications, and it provides a variety of features for creating high-quality plots. However, it does not support reading or writing data in the Apache Parquet file format.
Seaborn is a Python library for statistical visualization. It is built on top of Matplotlib, and it provides a number of features that make it easier to create effective statistical plots. However, it also does not support reading or writing data in the Apache Parquet file format.
Pandas is a Python library for data analysis. It provides a variety of features for working with structured data, including reading and writing data in a variety of formats.
However, it does not support the Apache Parquet file format natively. There are third-party libraries that can be used to read and write Parquet data with Pandas, but pyarrow is a more direct and efficient option.In conclusion, pyarrow is the best library for working with data stored in the Apache Parquet file format in Python. It is efficient, scalable, and supports a wide range of features.