Data visualization is the visual representation of data in order to effectively and interactively convey information to customers, clients as well as other stakeholders. It's a method to summarise your findings and present it in a way that aids understanding and assists in identifying trends or patterns. In this course, you'll learn to design attractive charts and graphs and modify the designs so that they are more efficient and pleasing to the people you are presenting them to. "A image is worth 1,000 words". We all know the phrase. This is especially true when trying to explain the insights gained from the analysis of massive data sets. Data visualization plays a crucial function in the presentation of both large and small scale data. One of the most important abilities of data scientists is the ability to create an engaging story by visualizing results and data in a comprehensible and engaging manner. Understanding how to use the power of software tools to visualize data can also help you to gather data, gain a better understanding of the data, and make better decisions. The primary purpose of this course is to help you look at data that, at first glance is not very meaningful and present it in a way that is understandable to the user. There are a variety of methods that have been created to present data visually, but for this class, we'll use a variety of visualization tools that are available in Python including Matplotlib seaborn, and Folium
