R and Python for Oceanographers: A Practical Guide with Applications

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R AND PYTHON
FOR OCEANOGRAPHERS
A Practical Guide with Applications
Copyright
1
Introduction to R and Python
	Introduction to R
	R environment
		Base system of R
		Add-on packages
	Installation of R
		Installation of R base software
		Installation of add-on packages
	Integrated development environments (IDEs) and editors for R
		Official R console and editor
		RStudio
	Useful R commands
	Getting help for R
	Introduction to Python
	Modules and packages in Python
	Python IDEs
	Installing Python and scientific Python distributions
		Using pip package
		Using package managers
		Using source files of packages
	Getting help for Python
	Some useful packages and libraries in R and Python for oceanography
	References
2
Data import and export in R and Python
	Object types in R
		Vectors
		Matrices
		Arrays
		Data frames
		Lists
		Factors
		Functions
	Data import in R
		Import from txt, dat, csv and Excel xls, xlsx files
		Import from netCDF4 file
		Import from mat files
		Import from SeaBird cnv files
		Import data from online databases
			Import tab delimited text data from LOBO-0010 Northwest Arm, Halifax, Canada
		Import csv.gz file from WOA13 V2
	Data export in R
		Export as txt, dat, csv and Excel xls, xlsx files
		Export as netCDF4 file
		Export as Matlab mat files
	Object types in Python
		Arrays in Numpy package
			Create an array
			Create array from existing data
		Series and data frame objects in Pandas package
			Pandas Series
			Pandas Data Frames
		User-defined functions in Python
	Data import in Python
		Import from txt, dat, csv, and Excel xls, xlsx files with Numpy loadtxt
		Import from Excel xls files with Pandas read_excel
		Import from Excel xlsx files with Pandas read_excel
		Import from netCDF4 file
		Import from Matlab mat files
		Import from Seabird cnv file
		Import data from online databases
			Import tab delimited text data from LOBO-0010 Northwest Arm, Halifax, Canada
			Import all data in a csv file
			Import block of data at defined ranges of rows and columns
			Subset data based on multiple criteria using column values
	Data export in Python
		Export as txt, dat, and csv files with Numpy savetxt
		Export as txt, dat and csv files with Pandas DataFrame.to_csv
		Export as xls, xlsx with Pandas ExcelWriter
		Export as netCDF4 files
		Export as Matlab mat files
	References
3
Plotting
	Plots in R
		High-level plotting functions
			plot() function
			Other high-level plotting functions
			Arguments to use with high-level plotting functions
			Low-level plotting functions
		Graphical parameters
			par() function
		Graphical parameters as arguments in graphics functions
		Most frequently used graphical parameters
		Plotting multiple figures
		Device drivers
		Example plots in R
	Plotting in Python
		Pyplot API
		Matplotlib API
	References
4
Physical oceanography examples
	Vertical profiling plots in R
	Time-series plots in R
	Temperature-salinity diagrams in R
	Maps in R
	Transect plots in R
	Surface plots in R
	Vertical profiling plots in Python
	Time series plots in Python
	Temperature-salinity diagrams in Python
	Maps in Python
	Transect plots in Python
	Surface plots in Python
	Animations in R and Python
	References
5
Chemical oceanography examples
	Vertical profiling plots in R
	Time-series plots in R
	Barplots in R
	Boxplots in R
	Pie charts in R
	3D plots in R
	Ternary plots in R
	Vertical profiling plots in Python
	Time-series plots in Python
	Barplots in Python
	Boxplots in Python
	Pie charts in Python
	3D plots in Python
	Ternary plots in Python
	References
Index
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