Boris Gorelik is a data scientist, algorithm developer, and data visualization lecturer. Currently working at Automattic, the company beyond WordPress.com, Jetpack, and other projects. Solving data-intense problems since 2001.

Workshop description:
Data visualization is an indispensable tool for any data scientist. It serves as a means to convey a message or explain a concept.   You would never settle for default settings of a machine learning algorithm. Instead, you would tweak them to obtain optimal results. Similarly, you should never stop with the default results you receive from a data visualization framework. Doing so leads to suboptimal results and makes you and your message less convincing.

After this workshop, you will be able to name three most common mistakes in data visualization, and learn how to apply them in your graphs.

During this workshop, a short theoretical introduction will be followed by three lab examples. We will use matplotlib in Jupyter notebooks to practice the knowledge. You are expected to have at least intermediate knowledge of Python, Jupyter notebook interface, and matplotlib object-oriented interface.

Timeline:
1. Theoretical introduction: three most common mistakes in data visualization (45 minutes)
2. Test case (LAB): Plotting several radically different time series on a single graph (45 minutes)
3. Test case (LAB): Bar chart as an effective alternative to a pie chart (45 minutes)
4. Test case (LAB): Pie chart as an effective alternative to a bar chart (45 minutes)

The time line includes some time for recess.