Which library in Python is commonly used for data manipulation and analysis in Data Science?

Pandas
Matplotlib
Scikit-Learn
TensorFlow

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:

  • Cleaning and munging data
  • Analyzing and visualizing data
  • Preparing data for machine learning
  • Building statistical models

Pandas is a powerful tool that can be used for a variety of data analysis tasks. It is easy to use and has a wide range of features. If you are working with data in Python, Pandas is a great library to have in your toolkit.

Here are some of the benefits of using Pandas:

  • It is fast and efficient.
  • It is easy to use.
  • It has a wide range of features.
  • It is well-documented.
  • It is open source.

If you are looking for a powerful tool for data analysis in Python, Pandas is a great option. It is easy to use and has a wide range of features.