# Introduction In data visualization, it is common to encounter missing data that needs to be plotted. In this tutorial, we will learn how to plot data with missing values using Matplotlib. We will explore three methods: removing undesired data points, masking points, and setting values to NaN. ## VM Tips After the VM startup is done, click the top left corner to switch to the **Notebook** tab to access Jupyter Notebook for practice. Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook. If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.
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