Mastering Data Visualization with Python

Visualize data using pandas, matplotlib and seaborn libraries for data analysis and data science

Created by: Sandeep Kumar, ­ Quality Gurus Inc.
Experienced Quality Director • Six Sigma Coach • Consultant

Created by: Abhin Chhabra
Senior Software Engineer

What Will I Learn?

• Understand which plots are suitable for different types of data, ensuring you select the most effective visualization method for your analysis.
• Visualize data by creating various graphs using the pandas, matplotlib, and seaborn libraries, enhancing your ability to communicate data insights.
• Master data visualization techniques to draw meaningful knowledge from your data, making informed decisions based on clear visual representations.
• Learn to create time-series line plots, bar plots, pie plots, histograms, density or KDE plots, and box-whisker plots using the pandas package.
• Explore matplotlib library to create time-series line plots, bar plots, pie plots, histograms, density or KDE plots, box-whisker plots, and scatter plots.
• Master the seaborn library to create relational plots (scatter and line plots), distribution plots, and categorical plots (strip, swarm, box, violin, point etc)
• Customize your plots by creating themes based on style, context, color palette, and font to enhance the visual appeal and clarity of your visualizations.
• Enhance your resume with advanced data visualization skills using Python, making you a competitive candidate in data science and analytics fields.

Requirements

• Some basic knowledge of Python is expected. However this course does include a quick overview of Python knowledge required for this course.

Target audience

• Data Science, Six Sigma and other professionals interested in data visualization
• Professionals interested in creating publication quality plots
• Professionals who are not happy with the plots created in MS Excel, and see them as dull and boring