Question

What libraries would you use to wrangle data in Python?

1) Pandas
2) NumPy
3) Matplotlib
4) Scikit-learn

Answer 1

The libraries commonly used for data wrangling in Python include Pandas, NumPy, Matplotlib, and Scikit-learn.

Step-by-step explanation:

In Python, there are several libraries that are commonly used for data wrangling:

1. Pandas: Pandas is a powerful library for data manipulation and analysis. It provides data structures like DataFrames and Series, which allow you to efficiently handle and analyze large datasets. It offers functions for cleaning, merging, transforming, and reshaping data.
2. NumPy: NumPy is a fundamental library for numerical computing in Python. It provides support for large, multi-dimensional arrays and matrices. NumPy is often used in conjunction with Pandas for advanced data manipulation tasks.
3. Matplotlib: Matplotlib is a plotting library that enables the creation of a wide variety of static, animated, and interactive visualizations in Python. It is commonly used for data visualization and exploration.

Scikit-learn: Scikit-learn is a popular machine learning library in Python. While its primary focus is on machine learning algorithms, it also offers various functionalities for data preparation, preprocessing, and feature selection.