Book Image

Hands-On Data Science with Anaconda

By : Yuxing Yan, James Yan
Book Image

Hands-On Data Science with Anaconda

By: Yuxing Yan, James Yan

Overview of this book

Anaconda is an open source platform that brings together the best tools for data science professionals with more than 100 popular packages supporting Python, Scala, and R languages. Hands-On Data Science with Anaconda gets you started with Anaconda and demonstrates how you can use it to perform data science operations in the real world. The book begins with setting up the environment for Anaconda platform in order to make it accessible for tools and frameworks such as Jupyter, pandas, matplotlib, Python, R, Julia, and more. You’ll walk through package manager Conda, through which you can automatically manage all packages including cross-language dependencies, and work across Linux, macOS, and Windows. You’ll explore all the essentials of data science and linear algebra to perform data science tasks using packages such as SciPy, contrastive, scikit-learn, Rattle, and Rmixmod. Once you’re accustomed to all this, you’ll start with operations in data science such as cleaning, sorting, and data classification. You’ll move on to learning how to perform tasks such as clustering, regression, prediction, and building machine learning models and optimizing them. In addition to this, you’ll learn how to visualize data using the packages available for Julia, Python, and R.
Table of Contents (15 chapters)

Package dependencies

There are two types of package dependencies. The first one is the package depending on the version of underlying software. For example, take the Octave package called statistics, available at https://octave.sourceforge.io/statistics. On February 22, 2018, it has a version of 1.3.0 and it requires an underlying Octave with a version of at least 4.0.0, as shown in the last line of the following screenshot:

The second type of dependency is between packages. Developers of various packages use many functions embedded in other developed packages. Not only does this save time, but it also means they don't have to reinvent the wheel. From the last line of the previous screenshot, we know that this package depends on another Octave package called io.

In the following, we show the process of installation. First, we download the ZIP file from https://octave.sourceforge...