Introduction to Python for Science and Engineering 2nd Edition by David J Pine ISBN 1032673958 9781032673950

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ISBN 10: 1032673958 
ISBN 13: 9781032673950
Author: David J Pine

Introduction to Python for Science and Engineering 2nd Table of contents:

Chapter 1 ▪ Introduction
1.1 introduction to python for science and engineering
1.2 installing python

Chapter 2 ▪ Launching Python
2.1 interacting with python: the ipython shell
2.2 the ipython shell
2.3 interactive python as a calculator
2.3.1 binary arithmetic operations in python
2.3.2 types of numbers
2.3.3 numbers as objects
2.4 variables and assignment
2.4.1 names and the assignment operator
2.4.2 legal and recommended variable names
2.4.3 reserved words in python
2.5 script files and programs
2.5.1 editors for python scripts
2.5.2 first scripting example
2.6 python modules
2.6.1 python modules and functions: a first look
2.6.2 some numpy functions
2.6.3 scripting example 2
2.6.4 different ways of importing modules
2.7 getting help: documentation in ipython
2.8 performing system tasks with ipython
2.8.1 magic commands
2.8.2 tab completion
2.8.3 recap of commands
2.9 programming errors
2.9.1 error checking
2.10 exercises

Chapter 3 ▪ Integrated Development Environments
3.1 programming and interacting with python
3.2 programming style and coding errors: pep 8 and linters
3.3 the spyder ide
3.3.1 autoformatting and linting in spyder
3.3.2 running python code in spyder
3.4 the jupyterlab ide
3.4.1 jupyter extensions
3.5 jupyter notebooks
3.6 launching a jupyter notebook
3.7 running programs in a jupyter notebook
3.8 annotating a jupyter notebook
3.8.1 adding headings and text
3.8.2 saving a jupyter notebook
3.8.3 editing and rerunning a notebook
3.8.4 quitting a jupyter notebook
3.8.5 working with an existing jupyter notebook

Chapter 4 ▪ Strings, Lists, Arrays, and Dictionaries
4.1 strings
4.1.1 unicode characters
4.2 lists
4.2.1 slicing lists
4.2.2 multidimensional lists
4.2.3 appending to lists
4.2.4 tuples
4.3 dictionaries
4.4 numpy arrays
4.4.1 creating arrays (1-d)
4.4.2 mathematical operations with arrays
4.4.3 slicing and addressing arrays
4.4.4 fancy indexing: boolean indexing
4.4.5 multidimensional arrays and matrices
4.4.6 broadcasting
4.4.7 differences between lists and arrays
4.5 objects
4.6 exercises

Chapter 5 ▪ Input and Output
5.1 keyboard input
5.2 screen output
5.2.1 formatting output with str.format()
5.2.2 formatting with f-strings
5.2.3 printing arrays
5.3 file input
5.3.1 reading data from a text file
5.3.2 reading data from an excel file: csv files
5.4 file output
5.4.1 writing data to a text file
5.4.2 writing data to a csv file
5.5 exercises

Chapter 6 ▪ Conditionals and Loops
6.1 conditionals
6.1.1 if, elif, and else statements
6.1.2 more about boolean variables, operators, and expressions
6.2 loops
6.2.1 while loops
6.2.2 for loops
6.2.3 loop control statements
6.2.4 loops and array operations
6.3 list comprehensions
6.4 handling exceptions
6.5 exercises

Chapter 7 ▪ Functions
7.1 user-defined functions
7.1.1 looping over arrays in user-defined functions
7.1.2 fast array processing for user-defined functions
7.1.3 functions with more than one input or output
7.1.4 type hints
7.1.5 positional and keyword arguments
7.1.6 variable number of arguments
7.1.7 passing a function name and its parameters as arguments
7.2 namespace and scope in python
7.2.1 scope: four levels of namespaces in python
7.2.2 variables and arrays created entirely within a function
7.2.3 passing lists and arrays to functions: mutable and immutable objects
7.3 anonymous functions: lambda expressions
7.4 numpy object attributes: methods and instance variables
7.5 example: linear least squares fitting
7.5.1 linear regression
7.5.2 linear regression with weighting: χ2
7.6 exercises

Chapter 8 ▪ Plotting
8.1 an interactive session with pyplot
8.2 basic plotting
8.2.1 specifying line and symbol types and colors
8.2.2 error bars
8.2.3 setting plotting limits and excluding data
8.2.4 subplots
8.3 logarithmic plots
8.3.1 semi-log plots
8.3.2 log-log plots
8.4 more advanced graphical output
8.4.1 an alternative syntax for a grid of plots
8.5 plots with multiple axes
8.5.1 plotting quantities that share one axis but not the other
8.5.2 two separate scales for a data set
8.6 plots with insets
8.7 mathematics and greek symbols
8.7.1 manual axis labeling
8.8 the structure of matplotlib: oop and all that
8.8.1 the backend layer
8.8.2 the artist layer
8.8.3 the pyplot (scripting) layer
8.9 contour and vector field plots
8.9.1 making a 2d grid of points
8.9.2 contour plots
8.9.3 streamline plots
8.9.4 vector field (quiver) plots
8.10 three-dimensional plots
8.10.1 cartesian coordinates
8.10.2 polar coordinates
8.11 exercises

Chapter 9 ▪ Numerical Routines: SciPy and NumPy
9.1 special functions
9.1.1 important note on importing scipy subpackages
9.2 spline fitting, smoothing, and interpolation
9.2.1 interpolating splines
9.2.2 smoothing splines
9.2.3 finding roots (zero crossings) of numerical data
9.3 curve fitting
9.3.1 linear fitting functions
9.3.2 polynomial fitting functions
9.3.3 nonlinear fitting functions
9.4 random numbers
9.4.1 initializing numpy’s random number generator
9.4.2 uniformly distributed random numbers
9.4.3 normally distributed random numbers
9.4.4 random distribution of integers
9.4.5 poisson distribution of random integers
9.5 linear algebra
9.5.1 basic computations in linear algebra
9.5.2 solving systems of linear equations
9.5.3 eigenvalue problems
9.6 solving nonlinear equations
9.6.1 single equations of a single variable
9.6.2 solving systems of nonlinear equations
9.7 numerical integration
9.7.1 single integrals of functions
9.7.2 double integrals
9.7.3 integrating numerical data
9.8 solving odes
9.8.1 a first-order ode
9.8.2 a second-order ode
9.9 discrete (fast) fourier transforms
9.9.1 continuous and discrete fourier transforms
9.9.2 the scipy fft library
9.10 exercises

Chapter 10 ▪ Python Classes: Encapsulation
10.1 a very simple class
10.2 a brief introduction to modules and packages
10.2.1 pythonpath
10.3 a class for reading and processing data
10.3.1 the data
10.3.2 the class
10.3.3 the code
10.4 a class of related functions
10.5 inheritance
10.6 exercises

Chapter 11 ▪ Data Manipulation and Analysis: Pandas
11.1 data structures: series and dataframe
11.1.1 series
11.1.2 dataframe
11.2 indexing dataframes
11.2.1 pandas iloc indexing
11.2.2 pandas loc indexing
11.3 reading data from files using pandas
11.3.1 reading from excel files saved as csv files
11.3.2 reading from an excel file
11.3.3 getting data from the web
11.4 extracting information from a dataframe
11.5 plotting with pandas
11.6 grouping and aggregation
11.6.1 the groupby method
11.6.2 iterating over groups
11.6.3 reformatting dataframes
11.6.4 custom aggregation of dataframes
11.7 exercises

Chapter 12 ▪ Animation
12.1 animating a sequence of images
12.1.1 simple image sequence
12.1.2 annotating and embellishing

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