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You’re a data analyst at Global Consensus Bureau, and your manager has asked you to determine how factors like education, hours worked per week, gender, and age relate to citizens’ incomes. Using pandas, you’ll pre-process data from a survey conducted by the U.S. Census Bureau. Then, you’ll create different charts to identify statistical relationships in data, using Python’s seaborn library, which provides custom functions for visual elements. When you’re done, you’ll know how to use seaborn to create visually appealing charts that reveal accurate and useful insights.
This liveProject is for data analysts, research scholars, and software engineers who would like to learn how to enhance their plotting skillset with Python’s seaborn library. To begin these liveProjects you’ll need to be familiar with the following:TOOLS
In this liveProject, you’ll learn to use seaborn to create visually appealing charts that reveal accurate and useful insights.
geekle is based on a wordle clone.