Data visualization is a key component in the data science process, from the initial stages of data exploration to the end game of communicating complicated results to one's audience. Making sense of patterns in data is often facilitated by human cognitive capabilities of pattern recognition, and graphical summaries of a large and complex dataset can often suggest particular directions for further quantitative analysis. There is of course an old adage that "seeing is believing", but in some cases wth complex datasets, it is sometimes the case that "seeing is understanding", in that useful data visualizations can help us to understand the data in its entirety (at least in broad strokes). In this topic, we introduce various techniques for visualizing different types of data and describe tools in the Python data science ecosystem to support those activities.