# Introduction This lab will guide you on how to use sparse data structures in the pandas library. This is useful in scenarios where we have large volumes of data, most of which are similar (like zero or NaN), hence can be represented more efficiently in memory. We will learn about the `SparseArray`, `SparseDtype`, sparse accessor, sparse calculation, and interaction with scipy sparse matrices. ## 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.
Click the virtual machine below to start practicing