Data Visualization with Python (PY-4)

Location: Virtual or On-site

Length: 3 Days

Price: $2,400 per student

Overview:

With so much data being continuously generated, developers with a knowledge of data analytics and data visualization are always in demand. With Data Visualization with Python, you'll learn how to use Python with NumPy, Pandas, Matplotlib, and Seaborn to create impactful data visualizations with real world, public data.

Data Visualization with Python takes a hands-on approach to the practical aspects of using Python to create effective data visuals. It contains multiple activities that use real-life business scenarios for you to practice and apply your new skills in a highly relevant context.

Learn why Fulcrum Forge is the best choice to be your training partner.

Course Objectives:

This course will provide you with knowledge of the following:

• Understand and use various plot types with Python

• Explore and work with different plotting libraries

• Understand and create effective visualizations

• Improve your Python data wrangling skills

• Work with industry-standard tools like Matplotlib, Seaborn, and Bokeh

• Understand different data formats and representations

Who Should Attend:

Data Visualization with Python is designed for developers and scientists, who want to get into data science or when to use data visualizations to enrich their personal and professional projects. You do not need any prior experience in data analytics and visualization, however, it'll help you to have some knowledge of Python and familiarity with high school level mathematics. Even though this is a beginner level course on data visualization, experienced developers will be able to improve their Python skills by working with real-world data.

Certification:

Not applicable.

Prerequisites:

• Introduction to Programming with Python®

Detailed Course Outline

Lesson 1: Importance of data visualization and data exploration

• Topic 1: Introduction to data visualization and its importance

• Topic 2: Overview of statistics

• Topic 3: A quick way to get a good feeling for your data

• Topic 4: NumPy

• Topic 5: Pandas

Lesson 2: All you need to know about plots

• Topic 1: Choosing the best visualization

• Topic 2: Comparison plots

• Topic 3: Relation plots

• Topic 4: Composition plots

• Topic 5: Distribution plots

• Topic 6: Geo plots

• Topic 7: What makes a good plot?

Lesson 3: Introduction to NumPy, Pandas, and Matplotlib

• Topic 1: Overview and differences of libraries

• Topic 2: Matplotlib

• Topic 3: Seaborn

• Topic 4: Geo plots with geoplotlib

• Topic 5: Interactive plots with bokeh

Lesson 4: Deep Dive into Data Wrangling with Python

• Topic 1: Matplotlib

• Topic 2: Pyplot basics

• Topic 3: Basic plots

• Topic 4: Legends

• Topic 5: Layouts

• Topic 6: Images

• Topic 7: Writing mathematical expressions

Lesson 5: Simplification through Seaborn

• Topic 1: From Matplotlib to Seaborn

• Topic 2: Controlling figure aesthetics

• Topic 3: Color palettes

• Topic 4: Multi-plot grids

Lesson 6: Plotting geospatial data

• Topic 1: Geoplotlib basics

• Topic 2: Tiles providers

• Topic 3: Custom layers

Lesson 7: Making things interactive with Bokeh

• Topic 1: Bokeh basics

• Topic 2: Adding Widgets

• Topic 3: Animated Plots

Lesson 8: Combining what we've learned

• Topic 1: Recap

• Topic 2: Free exercise

Lesson 9: Application in real life and Conclusion of course

• Topic 1: Applying Your Knowledge to a Real-life Data Wrangling Task

• Topic 2: An Extension to Data Wrangling

To discuss training options, call us at (888) 430-2456.