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)

Finding all R packages

For R-related packages, go to http://r-project.org first. Click on CRAN and choose a mirror location, then click Packages on the left-hand side. We can see two lists, as shown here:

On February 22, 2018, there are 12,173 R packages available. The first list contains all available packages sorted by their publication dates (that is, the dates they updated, or published if they were never updated). The second list is sorted by their names. If we just want to find relevant packages, either list will be fine. For example, for the first list, here is a snapshot of a few lines:

The first column shows when the packages were last updated, or published if no updates were available. The second column shows the names of the packages, while the last column offers a short description of the usage for each package. We can use keywords to find the packages we want...