Data Analysis in the Water and Environment -- Python Environment and Basics -- Python Essentials -- Exploratory Analysis of Hydrological Data -- Graphical Hydrological Data Analysis -- Curve Fitting and Regression Analysis -- Hydrological Time Series Analysis -- Common Hypothesis Testing -- Uncertainty Estimation -- Introduction -- Surface Flow Models -- Subsurface Flow Models -- Transport Phenomena -- Contaminant Transport Models -- Conclusion.

This textbook delves into the practical applications of surface and groundwater hydrology, as well as the environment. The Part I, "Practical Python for a Water and Environment Professional," guides readers through setting up a scientific computing environment and conducting exploratory data analysis and visualization using reproducible workflows. The Part II, "Statistical Modeling in Hydrology," covers regression models, time series analysis, and common hypothesis testing. The Part III, "Surface and Subsurface Water," illustrates the use of Python in understanding key concepts related to seepage, groundwater, and surface water flows. Lastly, the Part IV, "Environmental Applications," demonstrates the application of Python in the study of various contaminant transport phenomena.