ABC Bikes Inc. is considering launching a bike rental service in your area. As the company’s data analyst, your task is to provide decision-driving insights on bike rental trends. You’ll extract the relevant data from a publicly available dataset into a pandas data frame. Then, using Python plotting library Matplotlib, you’ll create line plots to visualize changes for bike rentals on a single day as well as over a specific time period, create a grouped bar plot to visualize a comparison of renting data for two years, create subplots with different chart types, and create a violin plot to visualize renting patterns over four seasons. When you’re done, you’ll know how to use Matplotlib to create accurate and informative 2D visualizations.

ABC Bikes Inc. is considering expanding its bike rental service to a new county. Your job, as the company’s data analyst, is to determine factors that impact the demand for rental bikes in that area. You’ll extract the relevant data from a publicly available dataset into a pandas data frame. Then, using Matplotlib’s mplot3d toolkit, you’ll plot 3D graphs to simultaneously visualize more than two data features, enabling you to determine useful patterns including how temperature, time of day, and month of year impact bike rentals. When you’re finished, you’ll know how to use Matplotlib to create, customize, and rotate your 3D plots to gather useful and interesting insights.

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.