About
The MicroPython pyboard is a compact electronic circuit board that runs MicroPython on the bare metal, giving you a low-level Python operating system that can be used to control all kinds of electronic projects. MicroPython is packed full of advanced features such as an interactive prompt, arbitrary precision integers, closures, list comprehension, generators, exception handling and more. Yet it is compact enough to fit and run within just 256k of code space and 16k of RAM. MicroPython aims to be as compatible with normal Python as possible to allow you to transfer code with ease from the desktop to a microcontroller or embedded system.
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About
The core of extensible programming is defining functions. Python allows mandatory and optional arguments, keyword arguments, and even arbitrary argument lists. Whether you're new to programming or an experienced developer, it's easy to learn and use Python. Python can be easy to pick up whether you're a first-time programmer or you're experienced with other languages. The following pages are a useful first step to get on your way to writing programs with Python! The community hosts conferences and meetups to collaborate on code, and much more. Python's documentation will help you along the way, and the mailing lists will keep you in touch. The Python Package Index (PyPI) hosts thousands of third-party modules for Python. Both Python's standard library and the community-contributed modules allow for endless possibilities.
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About
Imageio is a Python library that provides an easy interface to read and write a wide range of image data, including animated images, volumetric data, and scientific formats. It is cross-platform, runs on Python 3.5+, and is easy to install. Imageio is written in pure Python, so installation is easy. Imageio works on Python 3.5+. It also works on Pypy. Imageio depends on Numpy and Pillow. For some formats, imageio needs additional libraries/executables (e.g. ffmpeg), which imageio helps you to download/install. If something doesn’t work as it should, you need to know where to search for causes. The overview on this page aims to help you in this regard by giving you an idea of how things work, and - hence - where things may go sideways.
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About
statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests and statistical data exploration. An extensive list of result statistics is available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open-source Modified BSD (3-clause) license. statsmodels supports specifying models using R-style formulas and pandas DataFrames. Have a look at dir(results) to see available results. Attributes are described in results.__doc__ and results methods have their own docstrings. You can also use numpy arrays instead of formulas. The easiest way to install statsmodels is to install it as part of the Anaconda distribution, a cross-platform distribution for data analysis and scientific computing. This is the recommended installation method for most users.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
IoT Operating System for developers wanting to run microcontrollers
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Audience
Developers interested in a beautiful but advanced programming language
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Audience
Component Library solution for developers
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Audience
Users and anyone in search of a solution to calculate the estimation of many different statistical models
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Free
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Free
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Free
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Training
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Live Online
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Live Online
In Person
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Company InformationMicroPython
United Kingdom
micropython.org
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Company InformationPython
Founded: 1991
www.python.org
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Company Informationimageio
imageio.readthedocs.io/en/stable/
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Company Informationstatsmodels
www.statsmodels.org/stable/index.html
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Categories |
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Integrations
Apolo
CZ CELLxGENE Discover
Convex
CoppeliaSim
Dynamo BIM
Llama 3.2
LoginID
Lucidic AI
MLlib
Microsoft Genomics
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Integrations
Apolo
CZ CELLxGENE Discover
Convex
CoppeliaSim
Dynamo BIM
Llama 3.2
LoginID
Lucidic AI
MLlib
Microsoft Genomics
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Integrations
Apolo
CZ CELLxGENE Discover
Convex
CoppeliaSim
Dynamo BIM
Llama 3.2
LoginID
Lucidic AI
MLlib
Microsoft Genomics
|
Integrations
Apolo
CZ CELLxGENE Discover
Convex
CoppeliaSim
Dynamo BIM
Llama 3.2
LoginID
Lucidic AI
MLlib
Microsoft Genomics
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