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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
- An understanding of data science concepts
- Python programming experience
Audience
- Data analysts
- Data scientists
14 Hours
Delivery Options
Private Group Training
Our identity is rooted in delivering exactly what our clients need.
- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from £3800 online delivery, based on a group of 2 delegates, £1200 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
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Public Training
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