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We will be using several data visualization libraries in Python Matplotlib, Seaborn.
"A picture is worth a thousand words". We are all familiar with this expression. It especially applies when trying to explain the insight obtained from the analysis of increasingly large datasets. Data visualization plays an essential role in the representation of both small and large-scale data.
Welcome to this project-based course on Data Visualization with seaborn. In this project, you will create quick and interactive data visualizations with seaborn: a high-level data visualization library in Python inspired by matplotlib. You will explore the various features of the in-built Gapminder dataset, and produce interactive, publication-quality graphs to augment analysis.
One of the key skills of a data scientist is the ability to tell a compelling story, visualizing data and findings in an approachable and stimulating way. Learning how to leverage a software tool to visualize data will also enable you to extract information, better understand the data, and make more effective decisions. The main goal of this Data Visualization with Python course is to teach you how to take data that at first glance has little meaning and present that data in a form that makes sense to people. Various techniques have been developed for presenting data visually but in this course, we will be using several data visualization libraries in Python, namely Matplotlib, Seaborn, and Folium.