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    You will learn how to transform raw tables with numbers into interactive and human-readable charts. We will start with the overview of basic chart types, when to use a specific type and how to make it easy to read. Then we will learn how to create and adjust these plots using plotly in Python.  


    1. Basic types of charts (Line chart, Bar chart, Scatterplot, etc.).
    2. Some good/bad examples.
    3. Rule of thumb for creating a chart (sections 1-3 are ~1.5 hours in total).
    4. Plotly (~3.5 hours):
      1. Basic charts.
      2. Map charts.
      3. 3D charts.
      4. Subplots.
      5. Custom controls (buttons, sliders).
      6. Animations.

    Who is the workshop for:

    Data analysts, data scientists, data visualization specialists or any other people who are involved (interested) in creating data visualization.

    Key skills:

    After this workshop you will get the idea of how to:

    • Use the proper type chart for your data.
    • Create interactive plots using plotly packages.
    • Create multiple plots on one chart.
    • Create dynamic filters on a plot using buttons and sliders.
    • Create animation plots.

    Duration: 5 hours.

    Requirements: Python experience. Basic experience with visualization packages (like Matplotlib or Seaborn) is a plus.


    Ruslan Klymentiev

    Ruslan is a curriculum writer at DEVrepublik and Practice Instructor.
    He graduated from Odessa National Polytechnic University, a specialist in “Radio-electronic devices.”
    2.5 years of experience in Data Science.
    Interests: statistics, Data Visualization, CNN models and Computer Vision
    2 times received at Weekly Kernels Award on Kaggle.com
    Hobbies: climbing and hiking