Python for Data Visualization

Insights from data scientists can only be understood if they are presented in visually understandable ways so that nontechnical decision-makers can reach smart decisions. Fortunately, Python, the widely popular programming language, has a powerful data science ecosystem with libraries that allow anyone to create compelling and publication-ready visualizations. This course, taught by recognized Python instructor and blogger Michael Galarnyk, explores the pandas and Matplotlib libraries, and gives you an overview of other tools available like Jupyter notebooks and Anaconda Python 3 Distribution. With these and other Python capabilities, you’ll create memorable visualizations such as boxplots, bar graphs, line graphs, heat maps, histograms, and subplots. With this marketable skill set in hand, you’ll be able to increase efficiencies within any project and assist businesses looking to take advantage of the analytical power contained in their data.