5, 10 or 20 seats+ for your team - learn more
In this series of liveProjects, you’re a data analyst hired to visualize data for two different companies. In the first two liveProjects, you’ll help ABC Bikes Inc. make informed decisions about its dynamic bike rental service by providing important insights about bike rental trends. Using Matplotlib, you’ll create 2D and 3D plots to determine the busiest hours for rental bikes and how weather, time of day, and month of year impact rentals.
In the third liveProject, you’ll gather insights for the Global Consensus Bureau company to analyze data from a survey conducted by the U.S. Census Bureau to determine how factors like education, hours worked per week, gender, and age relate to citizens’ incomes. Using Python’s seaborn library, which provides functions for customizing visual elements, you’ll create visually appealing charts that identify the statistical relationships you’re interested in. When you’ve completed this series, you’ll have the experience and knowledge to use Python’s Matplotlib and seaborn libraries to create attractive visualizations that provide useful insights.
I think that for people that need to do quick visualization and analytics of data, this series will be a useful training tool.
The instructor put finished diagrams to give us an idea of what we were supposed to generate. This was very helpful.
I can definitely apply what I have learned as I need to create some graphs for usage of our archive.
These liveProjects are for early career data analysts. To begin these liveProjects you’ll need to be familiar with the following:TOOLS
In this liveProject series, you’ll create useful visualizations of interesting insights from data using Matplotlib and seaborn Python libraries.
geekle is based on a wordle clone.