To be honest, I just discovered that this IDE comes included in the distribution when writing this article. Spyder is a scientfic Python develeopment Environment.
Using Anaconda in an IDEīy default Spyder is included into the Anaconda distribution. The easy syntax makes it perfect for beginners to get fast results. Scikit-learn offers simple and efficient tools for data mining and machine learning. Matplotlib is Python 2D plotting library which produces high-quality figures and grpahs. They offer many Import/Output methods and in many projects you would read your data into a Pandas dataframe. Pandas is a library that offers easy to use data structures and data analysis and visualization tools. To learn more about NumPy refer to the official documentation. This includes mathematical, logical, shape manipulation, sorting and many more. It provides a multi-dimensional array object and offers fast operations on arrays. NumPy is a package for scientific computing.
However, since this post is mainly concerned with setting up an Anaconda environment, I won’t go much into detail. These packages are now presented a little bit more in detail. Some of the most frequently used packages for data scientists are NumPy, Pandas, Matplotlib and scikit-learn. By clicking on Environment you get a list of the installed packages. If everything was succesful you should see the version number.Īnother cool thing that comes included in the distribution is the Anaconda Navigator.
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