Python - Data Visualization and Dashboarding

• Efficiently visualize data sets using various Python libraries and tools.
• Create interactive dashboards to present data.
• You will learn techniques for working with batch and stream data.
• Learn to use advanced tools and libraries such as Voila, Panel, Streamlit, Vaex, and Apache Superset.

• Data analysts and data scientists who want to learn how to effectively visualize data and create interactive dashboards.
• Software developers who want to implement visualization components in their applications.
• IT professionals and business intelligence professionals who want to learn how to work with large data sets and streaming data.
• Anyone who has a basic understanding of Python and wants to expand their data visualization skills.

• Basic knowledge of Python at course level [PYTHON_INTRO].
• Basic knowledge of working with data using the Pandas library.
• Basic knowledge of data analysis concepts and techniques [PYTH_DATAAN].

• Expert commentary with practical demonstrations, computer exercises.

• Presentation of the material discussed in printed or online form.

Fundamentals of data visualization

• Introduction to data visualization.

  • Meaning and importance of data visualization
  • Types of graphs and their uses
  • Principles of effective data visualization

• Working with batch data

  • Importing and preparing data using Pandas and Vaex
  • Visualizing basic graphs using Matplotlib and Seaborn
  • Advanced visualization techniques (multiple sub-graphs, color palettes, interactive graphs with Plotly)

Interactive visualization and dashboards

• Interactive visualization with Plotly

  • Creating interactive charts (line, point, bar, 3D charts)
  • Adding interactive elements (hover information, interactive axes and legends)

• Creating dashboards using Voila

  • Introduction to Voila
  • Converting Jupyter notebooks to interactive dashboards
  • Working with interactive widgets and charts
  • Deploying Voila dashboards

Advanced dashboards and streaming data

• Dashboards with the Dashboard tool

  • Introduction to dashboards
  • Creating interactive dashboards
  • Integration with Bokeh, Matplotlib and Plotly
  • Adding interactive widgets and customizing layouts

• Visualization of stream data

  • Introduction to stream data
  • Using modules like Vaex and Pandas for streaming data
  • Interactive plots for stream data using Plotly and Panel

Creating interactive applications

• Streamlit

  • Introduction to Streamlit
  • Creating interactive applications and dashboards
  • Adding inputs, charts and widgets
  • Deploying Streamlit apps

• Apache Superset

  • Introduction to Apache Superset
  • Installation and Configuration
  • Working with databases and data sources
  • Creating and customizing dashboards
  • Interactive data visualization and filtering

Hands-on exercises and projects

• Practical exercise 1: Analysis and visualization of real batch data

  • Importing and preparing data
  • Creating visualizations according to specifications

• Practical exercise 2: Visualization of stream data

  • Setting up stream data
  • Interactive visualization for stream data

• Practical exercise 3: Creating a complex dashboard

  • Design and implement an interactive dashboard using Voila, Panel or Streamlit.

• Project presentation and discussion

  • Participants present their projects
  • Feedback from the trainer and other participants
  • Discussion on possible improvements and next steps

Summary and conclusion of the training

• Summary of the main points of the training
• Discussion and questions
• Presentation of the training certificate

Previous courses

Python - data analysis (Pandas) [PYTHON_DATAN]

Python II - advanced techniques [PYTHON_ADV]

Python I - introduction to programming [PYTHON_INTRO]