Öppna kurser

Data Visualization with Python

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

You will learn to:

  • Understand and use various plot types with Python.
  • Explore and work with different plotting libraries.
  • Understand and create effective visualisations.
  • Improve your Python data wrangling skills.
  • Work with industry-standard tools like Matplotlib, Seaborn, and Bokeh.
  • Understand different data formats and representations.

Data Visualisation with Python is designed for developers and scientists, who want to get into data science or want to use data visualisations to enrich their personal and professional projects.

You do not need any prior experience in data analytics and visualisation, 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 visualisation, experienced developers will be able to improve their Python skills by working with real-world data.

Importance of Data Visualisation and Data Exploration

  • Introduction to data visualisation and its importance
  • Overview of statistics
  • A quick way to get a good feeling for your data
  • NumPy
  • Pandas

All You Need to Know About Plots

  • Choosing the best visualisation
  • Comparison plots
  • Relation plots
  • Scatter plot
  • Bubble plot
  • Heatmap
  • Correlogram
  • Composition plots
  • Geo plots
  • What makes a good plot?

Introduction to NumPy, Pandas, and Matplotlib

  • Overview and differences of libraries
  • Matplotlib
  • Seaborn
  • Geo plots with geoplotlib
  • Interactive plots with bokeh

Deep Dive into Data Wrangling with Python

  • Matplotlib
  • Pyplot basics
  • Basic plots
  • Legends
  • Layouts
  • Images
  • Writing mathematical expressions

Simplification through Seaborn

  • From Matplotlib to Seaborn
  • Controlling figure aesthetics
  • Colour palettes
  • Multi-plot grids

Plotting Geospatial Data

  • Geoplotlib basics
  • Tiles providers
  • Custom layers

Making Things Interactive with Bokeh

  • Bokeh basics
  • Adding Widgets
  • Animated Plots

Application in Real Life and Conclusion of Course
Applying Your Knowledge to a Real-life Data Wrangling Task
An Extension to Data Wrangling


Kursen levereras genom utbildningspartner: Learning Tree