Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. Pandas provides a powerful and comprehensive toolset for working with data, including tools for reading and writing diverse files, data cleaning and wrangling, analysis and modeling, and visualization. Fields with widespread use of Pandas include: data science, finance, neuroscience, economics, advertising, web analytics, statistics, social science, and many areas of engineering.
In this course, you’ll learn how to use the pandas library and tools for data analysis and data structuring. Students will learn about DataFrames, basic plotting, indexing, and groupby. To help you learn how to work with data more effectively,
By the end of this course, students should have a good understanding of Pandas and gain proficiency using the Python Pandas library for data analysis.
Who is the target audience?
- Programmers and Developers
- Data analysts and business analysts
- Anyone interested in learning Pandas