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Python for water and environment

Record Type:	Electronic resources : Monograph/item
Title/Author:	Python for water and environment/ by Anil Kumar, Manabendra Saharia.
Author:	Anil Kumar.
other author:	Saharia, Manabendra.
Published:	Singapore :Springer Nature Singapore : : 2024.,
Description:	xix, 288 p. :ill. (chiefly col.), digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Hydrology - Computer simulation. -
Online resource:	https://doi.org/10.1007/978-981-99-9408-3
ISBN:	9789819994083

Python for water and environment
Anil Kumar.

Python for water and environment[electronic resource] /by Anil Kumar, Manabendra Saharia. - Singapore :Springer Nature Singapore :2024. - xix, 288 p. :ill. (chiefly col.), digital ;24 cm. - Innovations in sustainable technologies and computing,2731-8818. - Innovations in sustainable technologies and computing..

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.

ISBN: 9789819994083

Standard No.: 10.1007/978-981-99-9408-3doiSubjects--Topical Terms:

924161
Hydrology
--Computer simulation.

LC Class. No.: GB656.2.C63

Dewey Class. No.: 551.480285

Python for water and environment
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245 1 0 $a Python for water and environment $h [electronic resource] / $c by Anil Kumar, Manabendra Saharia.
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2024.
300 $a xix, 288 p. : $b ill. (chiefly col.), digital ; $c 24 cm.
490 1 $a Innovations in sustainable technologies and computing, $x 2731-8818
505 0 $a 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.
520 $a 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.
650 0 $a Hydrology $x Computer simulation. $3 924161
650 0 $a Python (Computer program language) $3 729789
650 1 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Python. $3 3201289
650 2 4 $a Data Analysis and Big Data. $3 3538537
650 2 4 $a Environmental and Sustainability Education. $3 3252534
700 1 $a Saharia, Manabendra. $3 3715692
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Innovations in sustainable technologies and computing. $3 3710662
856 4 0 $u https://doi.org/10.1007/978-981-99-9408-3
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)