Ivan Idris [Ivan Idris] - NumPy Cookbook - Second Edition
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- Book:NumPy Cookbook - Second Edition
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- Publisher:Packt Publishing
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- Year:2015
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NumPy Cookbook - Second Edition: summary, description and annotation
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Over 90 fascinating recipes to learn and perform mathematical, scientific, and engineering Python computations with NumPy
In Detail
NumPy has the ability to give you speed and high productivity. High performance calculations can be done easily with clean and efficient code, and it allows you to execute complex algebraic and mathematical computations in no time.
This book will give you a solid foundation in NumPy arrays and universal functions. Starting with the installation and configuration of IPython, youll learn about advanced indexing and array concepts along with commonly used yet effective functions. You will then cover practical concepts such as image processing, special arrays, and universal functions. You will also learn about plotting with Matplotlib and the related SciPy project with the help of examples. At the end of the book, you will study how to explore atmospheric pressure and its related techniques. By the time you finish this book, youll be able to write clean and fast code with NumPy.
What You Will Learn
- Learn advanced indexing and linear algebra
- Deal with missing stock price data using masked arrays
- Explore everything you need to know about image processing
- Dive into broadcasting and histograms
- Profile NumPy code and visualize the results
- Speed up your code with Cython
- Use universal functions and interoperability features
- Analyze your performance using Quality Assurance
- Learn about exploratory and predictive data analysis with NumPy
Downloading the example code for this book. You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.
Ivan Idris [Ivan Idris]: author's other books
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- additive smoothing
- URL /
- Anaconda
- URL /
- annual atmospheric pressure averages
- studying /
- append() function /
- arange() function
- URL /
- array interface
- using /
- URL /
- astype() function
- URL /
- atmospheric pressure
- exploring /
- extreme values, studying /
- audio filter
- designing /
- audio fragments
- repeating /
- autoregressive /
- BDD
- testing way /
- binomial proportion confidence
- URL /
- Boolean indexing
- abiut /
- bootstrapping /
- box plots
- URL /
- broadcasted arrays
- about /
- broadcasting
- URL /
- buffer interface /
- buffer protocol
- using /
- URL /
- Butterworth bandpass fillter
- URL /
- Canny filter /
- ceil() function
- URL /
- C functions
- calling /
- chararray
- used, for performing string operations /
- URL /
- choose() function /
- clustering
- about /
- Dow Jones stocks, with scikits-learn /
- code
- profiling, line_profiler used /
- profiling, cProfile extension used /
- analyzing, Pylint used /
- testing, docstrings used /
- testing, mocks used /
- compress() function
- URL /
- concatenate() function
- URL /
- copies
- creating /
- corners
- detecting /
- detecting, URL /
- cProfile extension
- used, for profiling code /
- cross-validation /
- URL /
- Cython
- about /
- installing /
- installing, from source archive /
- installing on Windows, URL /
- online documentation, URL /
- using, with NumPy /
- factorials, approximating /
- Cython code
- profiling /
- profiling, URL /
- data
- exchanging, MATLAB used /
- exchanging, Octave used /
- loading, as pandas objects from statsmodels /
- dataset
- example dataset, loading /
- URL /
- datetime64 type
- using /
- Wikipedia, using /
- day-to-day pressure range
- exploring /
- Debian
- PIL, installing /
- diff() function
- URL /
- dips
- trading periodically /
- docstrings
- used, for testing code /
- doctest
- URL /
- Dow Jones Industrial Average (DJI or DJIA) /
- easy_install
- used, for installing IPython /
- used, for installing SciPy /
- used, for installing PIL /
- used, for installing scikit-learn /
- URL /
- edge detection
- with Sobel filter /
- edges
- detecting /
- eig() function
- URL /
- eigenvector
- URL /
- Enthought
- URL /
- Enthought Canopy
- URL /
- escape time algorithm /
- exploratory data analysis
- about /
- URL /
- extreme values
- ignoring /
- factorials
- approximating, with Cython /
- fancy indexing
- about /
- URL /
- for ufuncs, at() method used /
- Fermat's factorization method
- URL /
- Fibonacci numbers
- summing /
- URL /
- Fibonacci series /
- frompyfunc() NumPy function
- URL /
- full() function
- used, for creating value initialized arrays /
- full_like() function
- used, for creating value initialized arrays /
- Gaussian filter
- URL /
- gfortran
- URL /
- Git
- URL /
- golden ratio
- about /
- URL /
- Google App Engine (GAE)
- installing /
- Google cloud
- NumPy code, deploying /
- Hello World program
- building /
- histogram() function
- URL /
- IIR
- URL /
- images
- resizing /
- loading, into memory maps /
- combining /
- blurring /
- interquartile range /
- intrayear average pressure
- studying /
- ipdb package
- URL /
- IPython
- about /
- URL /
- installing /
- installing, on Windows /
- installing, on Mac OS X /
- installing, on Linux /
- installing, with easy_install /
- installing, with pip /
- installing, from source /
- using, as shell /
- profiling with /
- debugging with /
- IPython magics documentation
- URL /
- IPython notebook
- running /
- running, in pylab mode /
- running, with inline figures /
- URL /
- exporting /
- exporting, options /
- saving /
- IPython shell
- using /
- URL /
- isfinite() function
- URL /
- ix_() function
- URL /
- jackknife resampling /
- Java virtual machine (JVM) /
- JPype
- installing /
- URL /
- NumPy array, sending /
- leastsq() function
- URL /
- Lena
- flipping /
- Lettuce documentation
- URL /
- line_profiler
- installing /
- used, for profiling code /
- line_profiler project
- URL /
- linspace() function /
- Linux
- IPython, installing /
- matplotlib, installing /
- SciPy, installing /
- list of locations
- indexing wth /
- load() function
- URL /
- log() function
- URL /
- log returns
- URL /
- Mac OS X
- IPython, installing /
- matplotlib, installing /
- SciPy, installing /
- Mandelbrot fractal
- URL /
- manual pages
- reading /
- Markov chain /
- masked array
- creating /
- MATLAB
- used, for exchanging data /
- matplotlib
- installing /
- installing, on Windows /
- installing, on Linux /
- installing, from source /
- installing, on Mac OS X /
- URL /
- matplotlib boxplot() function
- URL /
- maximum visibility
- analyzing /
- Wikipedia, URL /
- memory maps
- images, loading /
- meshgrid() function /
- mocks
- used, for testing code /
- URL /
- modf() function
- URL /
- moving average model
- pressure, predicting with /
- URL /
- nanmean() function
- used, for skipping NaNs /
- URL /
- NaNs
- skipping, nanstd() function used /
- skipping, nanmean() function used /
- skipping, nanvar() function used /
- nanstd() function
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