Python-and-Anaconda-Tricks.md

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+## Anaconda
+<img src="https://upload.wikimedia.org/wikipedia/en/c/cd/Anaconda_Logo.png" width="230" align="right">
+
+[Anaconda](https://www.anaconda.com/) is a platform that combines many important tools for Python development.
+
+You can [install Anaconda](https://docs.anaconda.com/anaconda/install/) for free. 
+
+Read more about Anaconda Navigator and its features [here](https://docs.anaconda.com/anaconda/navigator/). 
+
+## Virtual environments
+If you are not familiar with virtual environments you can read this article [Getting started with Python environments](https://towardsdatascience.com/getting-started-with-python-environments-using-conda-32e9f2779307).
+
+You can get more information about managing environments with Anaconda at [this link](https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html).
+
+## Python IDEs:  PyCharm, Spyder, Jupiter
+IDE, or integrated development environment, is software that combines common development tools in a single graphical interface. IDEs bring together important tools such as a code editor, a compiler or interpreter, and a debugger, making it easier to develop applications.
+
+In [this article](https://ssiddique.info/pycharm-vs-spyder-vs-jupyter.html), you can understand the differences between the main IDEs present in the Anaconda platform and choose the one that best fits your needs.  
+
+## Python tutorials
+[Python 3 : des fondamentaux aux concepts avancés du langage](https://www.fun-mooc.fr/courses/course-v1:UCA+107001+session02/about)
+
+[The Python Guru](http://thepythonguru.com/) is a beginner-friendly guide for non-programmers.
+
+[A Byte of Python](https://python.swaroopch.com/) is an introductory text for people with no previous programming experience.
+
+[DataCamp Python Tutorial](https://www.datacamp.com/courses/intro-to-python-for-data-science) is  a 4 hour tutorial focuses on Python specifically for Data Science. It has interactive exercises and video classes.
+
+Source and other tutorials: [Python for Non-Programmers](https://wiki.python.org/moin/BeginnersGuide/NonProgrammers)
+
+## Python packages
+### What is a Python packages?
+A Python package is a collection of ready-made modules and functions that you can use in your code. This way it is not necessary to program common functions every time you need to use them. To use these packages you need to install them on your machine and import them at the beginning of your code.
+
+*Note: You can find the terms module, library and package. They are different, however,  in this context we can treat them as synonymous.*
+
+### Main Python packages for science
+The most common libraries used by data scientists and engineers are:
+
+[NumPy](https://numpy.org/) contains a multi-dimensional array and matrix data structures.
+
+[SymPy](https://www.sympy.org/pt/index.html) for symbolic mathematics and provides computer algebra capabilities.
+
+[SciPy](https://www.scipy.org/)  includes modules for statistics, optimization, integration, linear algebra, signal and image processing.
+
+[Pandas](https://pandas.pydata.org/) for data manipulation and analysis with numerical tables and time series.
+
+[Pillow](https://python-pillow.org/) and [OpenCV](https://opencv.org/) for image processing. Plus [PyDIC](https://gitlab.com/damien.andre/pydic)  for local digital image correlation analysis.
+
+[Matplotlib](https://matplotlib.org/) allows the creation of static, animated and interactive visualizations.
+
+[VTK](https://pypi.org/project/vtk/) allows image processing, 3D graphics, volume rendering and visualization.
+
+[PyVista](https://docs.pyvista.org/), [PyACVD](https://github.com/pyvista/pyacvd) and [Meshio](https://pypi.org/project/meshio/) for mesh creation and plotting.
+
+In addition, the most used libraries for the development of artificial intelligence, with machine learning  and deep learnins methods are [scikit-learn](https://scikit-learn.org/stable/), [TensorFlow](https://www.tensorflow.org/) and [Keras](https://keras.io/).
+
+### How to install a package or module
+To install any package, run the following command in Anaconda PowerShell Prompt (Change *NamePackage* to the name of the package or module you want to install):
+
+`python -m pip install NamePackage`
+
+For more information about installing Python packages access the [Python documentation](https://docs.python.org/3/installing/index.html).
+
+It is worth mentioning that when installing Anaconda several important packages are already installed by default. To check which packages are already installed, as well as which version, run following command in Anaconda PowerShell Prompt:
+
+`conda list`
+
+### How to use a package or module
+After installing a package on your work environment, to use a package in your script you must `import` it. 
+
+[Here](https://www.digitalocean.com/community/tutorials/how-to-import-modules-in-python-3#importing-modules) you will find instructions on how to do it. 
+
+## Python documentation
+Here you can access the official [Python documentation](https://docs.python.org/3/).
+It is also worth mentioning that each package has its own documentation that explains in detail functions and modules. 
+
+It is also important to consult the [good practices guide](https://docs.python-guide.org/writing/style/) in order to keep your code organized, readable and standardized.
+
+## Sources
+https://www.python.org/
+
+https://www.datacamp.com/community/tutorials/data-science-python-ide
+
+https://activewizards.com/blog/top-15-libraries-for-data-science-in-python/
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