In this one-hour of hands-on guided project, you can easily learn how to analyze data using pandas, a popular Python library used for data analysis. This project will teach you how to analyze credit risk on a client dataset using the pandas library.
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One of the most commonly used tools in data science, pandas is a Python library used to load, process, and analyze datasets using SQL-like queries. Pandas offers several advantages, such as data representation, simpler lines of code, and the ability to handle large sets of data. A number of academic and commercial domains, including finance, economics, statistics, web analytics, and other entities, use pandas as part of their data analytics toolkit.
In this hands-on guided project, you will learn to perform preliminary data analysis and credit risk analysis on a credit card client dataset using the Python library pandas. You will learn how to import required libraries, explore datasets, analyze data, and visualize the dataset. By the end of this project, you will have learned the fundamentals of data analysis using pandas and developed job-ready skills.
You will be provided with access to a Cloud based-IDE which has all of the required software, including Python pandas, pre-installed. All you need is a recent version of a modern web browser to complete this project.
What you'll learn
After completing this hands-on guided project, you’ll be able to:
- Explore a dataset and perform calculations using its data
- Build dependencies among existing attributes of a dataset
- Visualize the results of data analysis with various plot types
