Book Image

Jupyter for Data Science

By : Dan Toomey
Book Image

Jupyter for Data Science

By: Dan Toomey

Overview of this book

Jupyter Notebook is a web-based environment that enables interactive computing in notebook documents. It allows you to create documents that contain live code, equations, and visualizations. This book is a comprehensive guide to getting started with data science using the popular Jupyter notebook. If you are familiar with Jupyter notebook and want to learn how to use its capabilities to perform various data science tasks, this is the book for you! From data exploration to visualization, this book will take you through every step of the way in implementing an effective data science pipeline using Jupyter. You will also see how you can utilize Jupyter's features to share your documents and codes with your colleagues. The book also explains how Python 3, R, and Julia can be integrated with Jupyter for various data science tasks. By the end of this book, you will comfortably leverage the power of Jupyter to perform various tasks in data science successfully.
Table of Contents (17 chapters)
Title Page
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

Make a prediction using R


We can perform the same analysis using R in a notebook. The functions are different for the different language, but the functionality is very close.

We use the same algorithm:

  • Load the dataset
  • Split the dataset into training and testing partitions
  • Develop a model based on the training partition
  • Use the model to predict from the testing partition
  • Compare predicted versus actual testing

The coding is as follows:

#load in the data set from uci.edu (slightly different from other housing model)housing <- read.table("http://archive.ics.uci.edu/ml/machine-learning-databases/housing/housing.data")#assign column namescolnames(housing) <- c("CRIM", "ZN", "INDUS", "CHAS", "NOX",                  "RM", "AGE", "DIS", "RAD", "TAX", "PRATIO",                  "B", "LSTAT", "MDEV")#make sure we have the right data being loadedsummary(housing)      CRIM                ZN             INDUS            CHAS         Min.   : 0.00632   Min.   :  0.00   Min.   : 0.46   Min.   :0.00000 ...