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)

Summary

In this chapter, we have introduced some basic concepts, such as the reasons why we use Anaconda, and the advantages of using full-fledged Anaconda and/or its baby version, Miniconda. Then, it was shown that without installing Anaconda, we could still use it by visiting a designated website. We could also test a few simple programs there, writing in R, Python, Julia, or Octave.

In Chapter 2, Anaconda Installation, we will show you how to install Anaconda and test if the installation is successful. We will look at how to launch Jupyter, how to launch Python, Spyder, and R, and how to find related help. Most of those concepts or procedures are quite basic, so readers who are confident with those basic concepts can skip this chapter, Chapter 2, Anaconda Installation, and go to Chapter 3, Data Basics, directly.