Python for Water and Environment (Hardcover). Questo articolo non è disponibile.
Lingua: inglese
Editore: Springer Verlag, Singapore, Singapore, 2024
- Prima edizione
- Rilegato
- Nuovo

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Venditore AbeBooks dal 12 ottobre 2005
Condizione: Nuovo
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Descrizione dell’articolo da parte del venditore
Hardcover. 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…
Codice articolo 9789819994076
- Titolo
- Python for Water and Environment (Hardcover)
- Autore
- Anil Kumar
- Editore
- Springer Verlag, Singapore, Singapore
- Anno di pubblicazione
- 2024
- Condizione
- new
- Rilegatura
- Hardcover
- Lingua
- inglese
- ISBN 10
- 9819994071
- ISBN 13
- 9789819994076
- Edizione
- prima edizione
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.
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