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By Robert Johansson

Numerical Python via Robert Johansson exhibits you ways to leverage the numerical and mathematical modules in Python and its typical Library in addition to renowned open resource numerical Python programs like NumPy, FiPy, matplotlib and extra to numerically compute strategies and mathematically version purposes in a few components like giant info, cloud computing, monetary engineering, company administration and more.

After studying and utilizing this publication, you'll get a few takeaway case research examples of purposes that may be present in components like enterprise administration, significant data/cloud computing, monetary engineering (i.e., techniques buying and selling funding alternatives), or even games.

Up till very lately, Python was once typically considered as only a internet scripting language. good, computational scientists and engineers have lately stumbled on the flexibleness and gear of Python to do extra. vast facts analytics and cloud computing programmers are seeing Python's substantial use. monetary engineers also are now utilizing Python of their paintings. Python looks evolving as a language which may even rival C++, Fortran, and Pascal/Delphi for numerical and mathematical computations.

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The IPython notebook files are stored in a JSON file format using the file name extension ipynb. An IPython notebook is not pure Python code, but if necessary the Python code in a notebook can easily be extracted using either “File ➤ Download as ➤ Python,” or using the IPython utility nbconvert (see below). 15 Chapter 1 ■ Introduction to Computing with Python Figure 1-5. A newly created and empty IPython notebook Cell Types The main content of the notebooks, below the menu bar and the toolbar, is organized in input and output cells.

When executing Python source code files from the editor, the namespace variables created in the script are retained in the IPython or Python session in the console. This is an important feature that makes Spyder an interactive computing environment, in addition to a traditional IDE application, since it allows exploring the values of variables after a script has finished executing. Spyder supports having multiple Python and IPython consoles opened simultaneously, and, for example, a new IPython console can be launched through the “Consoles – Open an IPython console” menu.

The basic numerical data types supported in NumPy are shown in Table 2-2. Non-numerical data types, such as strings, objects, and user-defined compound types are also supported. Table 2-2. Basic numerical data types available in NumPy dtype Variants Description int int8, int16, int32, int64 Integers. uint uint8, uint16, uint32, uint64 Unsigned (non-negative) integers. bool bool Boolean (True or False). float float16, float32, float64, float128 Floating-point numbers. complex complex64, complex128, complex256 Complex-valued floating-point numbers.

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