Data Visualization with Python Training Course
Data visualization involves converting raw data into graphical and visual formats to uncover patterns or trends. This course emphasizes the creation of data visualizations using Python, providing practical insights for various common applications.
This instructor-led, live training (available online or onsite) is designed for data analysts and data scientists aiming to utilize Python for constructing interactive data visualizations directly through code.
Upon completion of this training, participants will be capable of:
- Configuring the essential development environment to begin creating data visualizations with Python.
- Gaining a comprehensive understanding of core data visualization concepts, use cases, and relevant tools.
- Exploring various Python libraries such as Matplotlib, Seaborn, Bokeh, and Folium.
- Learning to generate line plots, statistical graphs, geo-spatial maps, and other complex visualizations using Python.
- Applying best practices and techniques for effectively presenting and interpreting data.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practice sessions.
- Hands-on implementation within a live laboratory environment.
Customization Options
- To request customized training for this course, please reach out to us to make arrangements.
Course Outline
Introduction
- Overview of data visualization core concepts
- Visualization techniques and tools
Getting Started
- Installing the Python libraries (Matplotlib, Seaborn, Bokeh, and Folium)
- Use cases and practical examples
Creating Line Plots and Graphs with Matplotlib
- Creating basic line plots
- Adding styles, axis, and labels
- Combining multiple plots
- Creating bar charts, pie charts and histograms
Building Complex Visualizations with Seaborn
- Visualizing Pandas DataFrame
- Plotting bars and aggregates
- Implementing KDE, Box, and Violin plots
- Analyzing statistical distributions
Making Visualizations Interactive with Bokeh
- Plotting with basic glyphs
- Creating layouts for multiple visualizations
- Styling and visual attributes
- Adding interactivity (interactive legends, hover actions, and widgets)
- Implementing linked selections
Visualizing Geospatial Data with Folium
- Plotting interactive maps
- Using layers and tiles
- Adding markers and paths
Troubleshooting
Summary and Next Steps
Requirements
- Familiarity with data science concepts
- Experience with Python programming
Target Audience
- Data analysts
- Data scientists
Need help picking the right course?
southafrica@nobleprog.co.za or +27 (0)10 005 5793
Data Visualization with Python Training Course - Enquiry
Testimonials (1)
workshops, practical examples
Martin Stuparek - Orange Slovensko, a.s.
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