The correct answer is A. Pandas.
Pandas is a Python library that provides fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language.
Pandas is well suited for many different kinds of data analysis, including:
- Data wrangling and cleaning
- Data analysis and visualization
- Time series analysis
- Financial analysis
- Scientific computing
Pandas is a very popular library, and is used by many data scientists and analysts. It is also used by many companies, including Google, Facebook, and Twitter.
Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations, and narrative text. Jupyter Notebooks are a powerful tool for data exploration and analysis, and they are widely used by data scientists and analysts.
Seaborn is a Python data visualization library based on Matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. Seaborn is well suited for data exploration and analysis, and it is used by many data scientists and analysts.
However, Pandas is the most commonly used Python library for data exploration and data cleaning tasks. It provides interactive and user-friendly interfaces that make it easy to work with data. Pandas also has a wide range of features that make it well suited for a variety of data analysis tasks.