This tutorial will introduce how to analyze three dimensional stacked and volumetric images in Python, mainly using scikit-image. We start the tutorial checking a brief overview of scikit-image and how it relates to packages in the scientific Python ecosystem, such as NumPy, SciPy and matplotlib. Then, we discuss how to process two and three dimensional data through several steps: first, we will pre-process the data using filtering, binarization and segmentation techniques. After that, we cover how to inspect, count and measure attributes of objects and regions of interest in the data. At the end, we present the visualization of large 3D data. Real-world examples are given from domains such as materials science and biology.