Python is an open-source programming language frequently used by researchers for data exploration and visualization. Several existing python libraries used for data visualization are matplotlib, seaborn, plotly, bokeh, and ggplot. A comparative analysis of these libraries is presented in along with their pros and cons. These libraries are used to exploit a publicly available dataset on titanic. The plots for same data are generated using these libraries and examined further. Matplotlib has been proven flexible to produce complex plots. Seaborn has easy interface and reduces the complexity. Plotly has been used to generate interactive visualizations with features such as pan and zoom. Bokeh has been used to create dashboards, while altair has produced declarative plots. Finally, ggplot has been used by researchers working on R language, and “grammar of graphics” approach has been adapted. It has been observed that no single library has been proven effective for visualization with all requirements. This paper provides a foundation for future researchers to enhance Python visualization tools.