Data analysis involves a number of steps. With Python, you can import data, visualize data, and perform descriptive statistical analysis. You can also group data and perform Analysis of Variance (ANOVA) tests.

Python, a popular programming language used in data analysis, provides a wide range of libraries and tools for handling, cleaning, and visualizing data. Python’s simplicity, versatility, and integration with other technologies make it a valuable tool for data analysts and scientists in many industries.

You’ll begin this guided project by importing data from multiple sources using Python. You’ll then analyze individual feature patterns using visualization techniques to get a better understanding of the data. Next, you’ll perform descriptive statistical analysis to summarize the data and gain insights into its distribution and relationships. You’ll learn the basics of grouping data to compare and analyze subsets of data. You will also study the concepts of correlation and causation to understand the relationship between different features of the data. Finally, you will learn about ANOVA, a statistical method to determine the difference between two or more means. 

After completing this project, you’ll be ready to apply your new Python skills for data analysis and prediction modeling.

After completing this project, you’ll be able to:

 For this project, you will need:

You’ll have access to a Cloud-based IDE that includes all of the required software, including a Python environment, pre-installed. All you need is a recent version of a modern web browser to complete this project.