Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletter Hub
Free Learning
Arrow right icon
timer SALE ENDS IN
0 Days
:
00 Hours
:
00 Minutes
:
00 Seconds
Jupyter for Data Science
Jupyter for Data Science

Jupyter for Data Science: Exploratory analysis, statistical modeling, machine learning, and data visualization with Jupyter

eBook
€17.99 €26.99
Paperback
€32.99
Subscription
Free Trial
Renews at €18.99p/m

What do you get with a Packt Subscription?

Free for first 7 days. $19.99 p/m after that. Cancel any time!
Product feature icon Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!
Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon Thousands of reference materials covering every tech concept you need to stay up to date.
Subscribe now
View plans & pricing
Table of content icon View table of contents Preview book icon Preview Book

Jupyter for Data Science

Working with Analytical Data on Jupyter

Jupyter does none of the heavy lifting for analyzing data: all the work is done by programs written in a selected language. Jupyter provides the framework to run a variety of programming language modules. So, we have a choice how we analyze data in Jupyter.

A popular choice for data analysis programming is Python. Jupyter does have complete support for Python programming. We will look at a variety of programming solutions that might tax such a support system and see how Jupyter fairs.

Data scraping with a Python notebook

A common tool for data analysis is gathering the data from a public source such as a website. Python is adept at scraping websites for data. Here, we look at an example that loads stock price information from Google Finance data.

In particular, given a stock symbol, we want to retrieve the last year of price ranges for that symbol.

One of the pages on the Google Finance site will give the last years' worth of price data for a security company. For example, if we were interested in the price points for Advanced Micro Devices (AMD), we would enter the following URL:

https://www.google.com/finance/historical?q=NASDAQ:AMD

Here, NASDAQ is the stock exchange that carries the AMD security. On the resultant Google page, there is a table of data points of interest, as seen in the following partial screenshot.

Like many sites that you will be attempting...

Using heavy-duty data processing functions in Jupyter

Python has several groups of processing functions that can tax computer system power. Let us use some of these in Jupyter and determine if the functionality performs as expected.

Using NumPy functions in Jupyter

NumPy is a package in Python providing multidimensional arrays and routines for array processing. We bring in the NumPy package using import * from numpy statement. In particular, the NumPy package defines the array keyword, referencing a NumPy object with extensive functionality.

The NumPy array processing functions run from the mundane, such as min() and max() functions (which provide the minimum and maximum values over the array dimensions provided), to...

Using SciPy in Jupyter

SciPy is an open source library for mathematics, science and, engineering. With such a wide scope, there are many areas we can explore using SciPy:

  • Integration
  • Optimization
  • Interpolation
  • Fourier transforms
  • Linear algebra
  • There are several other intense sets of functionality as well, such as signal processing

Using SciPy integration in Jupyter

A standard mathematical process is integrating an equation. SciPy accomplishes this using a callback function to iteratively calculate out the integration of your function. For example, suppose that we wanted to determine the integral of the following equation:

We would use a script like the following. We are using the definition of pi from the standard math...

Expanding on panda data frames in Jupyter

There are more functions built-in for working with data frames than we have used so far. If we were to take one of the data frames from a prior example in this chapter, the Titanic dataset from an Excel file, we could use additional functions to help portray and work with the dataset.

As a repeat, we load the dataset using the script:

import pandas as pd
df = pd.read_excel('http://biostat.mc.vanderbilt.edu/wiki/pub/Main/DataSets/titanic3.xls')

We can then inspect the data frame using the info function, which displays the characteristics of the data frame:

df.info()  

Some of the interesting points are as follows:

  • 1309 entries
  • 14 columns
  • Not many fields with valid data in the body column—most were lost
  • Does give a good overview of the types of data involved

We can also use the describe function, which gives us a statistical...

Summary

In this chapter, we looked at some of the more compute intensive tasks that might be performed in Jupyter. We used Python to scrape a website to gather data for analysis. We used Python NumPy, pandas, and SciPy functions for in-depth computation of results. We went further into pandas and explored manipulating data frames. Lastly, we saw examples of sorting and filtering data frames.

In the next chapter, we will make some predictions and use visualization to validate our predictions.

Left arrow icon Right arrow icon
Download code icon Download Code

Key benefits

  • Get the most out of your Jupyter notebook to complete the trickiest of tasks in Data Science
  • Learn all the tasks in the data science pipeline—from data acquisition to visualization—and implement them using Jupyter
  • Get ahead of the curve by mastering all the applications of Jupyter for data science with this unique and intuitive guide

Description

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.

Who is this book for?

This book targets students and professionals who wish to master the use of Jupyter to perform a variety of data science tasks. Some programming experience with R or Python, and some basic understanding of Jupyter, is all you need to get started with this book.

What you will learn

  • Understand why Jupyter notebooks are a perfect fit for your data science tasks
  • Perform scientific computing and data analysis tasks with Jupyter
  • Interpret and explore different kinds of data visually with charts, histograms, and more
  • Extend SQL s capabilities with Jupyter notebooks
  • Combine the power of R and Python 3 with Jupyter to create dynamic notebooks
  • Create interactive dashboards and dynamic presentations
  • Master the best coding practices and deploy your Jupyter notebooks efficiently

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : Oct 20, 2017
Length: 242 pages
Edition : 1st
Language : English
ISBN-13 : 9781785880070
Category :
Languages :
Concepts :
Tools :

What do you get with a Packt Subscription?

Free for first 7 days. $19.99 p/m after that. Cancel any time!
Product feature icon Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!
Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon Thousands of reference materials covering every tech concept you need to stay up to date.
Subscribe now
View plans & pricing

Product Details

Publication date : Oct 20, 2017
Length: 242 pages
Edition : 1st
Language : English
ISBN-13 : 9781785880070
Category :
Languages :
Concepts :
Tools :

Packt Subscriptions

See our plans and pricing
Modal Close icon
€18.99 billed monthly
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Simple pricing, no contract
€189.99 billed annually
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just €5 each
Feature tick icon Exclusive print discounts
€264.99 billed in 18 months
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just €5 each
Feature tick icon Exclusive print discounts

Frequently bought together


Stars icon
Total 116.97
Pandas Cookbook
€41.99
Jupyter for Data Science
€32.99
Learning Jupyter
€41.99
Total 116.97 Stars icon

Table of Contents

10 Chapters
Jupyter and Data Science Chevron down icon Chevron up icon
Working with Analytical Data on Jupyter Chevron down icon Chevron up icon
Data Visualization and Prediction Chevron down icon Chevron up icon
Data Mining and SQL Queries Chevron down icon Chevron up icon
R with Jupyter Chevron down icon Chevron up icon
Data Wrangling Chevron down icon Chevron up icon
Jupyter Dashboards Chevron down icon Chevron up icon
Statistical Modeling Chevron down icon Chevron up icon
Machine Learning Using Jupyter Chevron down icon Chevron up icon
Optimizing Jupyter Notebooks Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
(2 Ratings)
5 star 0%
4 star 0%
3 star 0%
2 star 0%
1 star 100%
Steve Gailey Nov 18, 2017
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
I don't think I have ever read a book so devoid of actual content. The book starts with an overly simplistic introduction to Jupiter which consists of nothing more than a brief explanation of each menu option. No discussion of distributions, installation or configuration options. No discussion of loading alternate kernels etc. So it is clearly for beginners. Except the book then launches into and example of using the Black Scholes model for option call pricing. No real explanation of what that is or how it works. So this is a finance book for experts? No because two pages further on and we are doing gamblin analysis in R. Listing after listing on apparently random subjects with no introduction, no explanation of either the code or the concepts. They are irrelevant to Jupiter for the most part and I can't see what they are trying to teach you. Truly a dreadful book - It is the first and only time I wish I had never waster my money on a book. I hope I never meet the author at a party - He must be real hard work to talk to!
Amazon Verified review Amazon
Jesse Lethe Dec 07, 2017
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
Text mixes Python and R on the examples. This makes it hard for those knowing only one of the two languages. Furthermore, author jumps into different subjects, expanding too much time on topics that are irrelevant to either Jupyter or Data Sciences.
Amazon Verified review Amazon
Get free access to Packt library with over 7500+ books and video courses for 7 days!
Start Free Trial

FAQs

What is included in a Packt subscription? Chevron down icon Chevron up icon

A subscription provides you with full access to view all Packt and licnesed content online, this includes exclusive access to Early Access titles. Depending on the tier chosen you can also earn credits and discounts to use for owning content

How can I cancel my subscription? Chevron down icon Chevron up icon

To cancel your subscription with us simply go to the account page - found in the top right of the page or at https://subscription.packtpub.com/my-account/subscription - From here you will see the ‘cancel subscription’ button in the grey box with your subscription information in.

What are credits? Chevron down icon Chevron up icon

Credits can be earned from reading 40 section of any title within the payment cycle - a month starting from the day of subscription payment. You also earn a Credit every month if you subscribe to our annual or 18 month plans. Credits can be used to buy books DRM free, the same way that you would pay for a book. Your credits can be found in the subscription homepage - subscription.packtpub.com - clicking on ‘the my’ library dropdown and selecting ‘credits’.

What happens if an Early Access Course is cancelled? Chevron down icon Chevron up icon

Projects are rarely cancelled, but sometimes it's unavoidable. If an Early Access course is cancelled or excessively delayed, you can exchange your purchase for another course. For further details, please contact us here.

Where can I send feedback about an Early Access title? Chevron down icon Chevron up icon

If you have any feedback about the product you're reading, or Early Access in general, then please fill out a contact form here and we'll make sure the feedback gets to the right team. 

Can I download the code files for Early Access titles? Chevron down icon Chevron up icon

We try to ensure that all books in Early Access have code available to use, download, and fork on GitHub. This helps us be more agile in the development of the book, and helps keep the often changing code base of new versions and new technologies as up to date as possible. Unfortunately, however, there will be rare cases when it is not possible for us to have downloadable code samples available until publication.

When we publish the book, the code files will also be available to download from the Packt website.

How accurate is the publication date? Chevron down icon Chevron up icon

The publication date is as accurate as we can be at any point in the project. Unfortunately, delays can happen. Often those delays are out of our control, such as changes to the technology code base or delays in the tech release. We do our best to give you an accurate estimate of the publication date at any given time, and as more chapters are delivered, the more accurate the delivery date will become.

How will I know when new chapters are ready? Chevron down icon Chevron up icon

We'll let you know every time there has been an update to a course that you've bought in Early Access. You'll get an email to let you know there has been a new chapter, or a change to a previous chapter. The new chapters are automatically added to your account, so you can also check back there any time you're ready and download or read them online.

I am a Packt subscriber, do I get Early Access? Chevron down icon Chevron up icon

Yes, all Early Access content is fully available through your subscription. You will need to have a paid for or active trial subscription in order to access all titles.

How is Early Access delivered? Chevron down icon Chevron up icon

Early Access is currently only available as a PDF or through our online reader. As we make changes or add new chapters, the files in your Packt account will be updated so you can download them again or view them online immediately.

How do I buy Early Access content? Chevron down icon Chevron up icon

Early Access is a way of us getting our content to you quicker, but the method of buying the Early Access course is still the same. Just find the course you want to buy, go through the check-out steps, and you’ll get a confirmation email from us with information and a link to the relevant Early Access courses.

What is Early Access? Chevron down icon Chevron up icon

Keeping up to date with the latest technology is difficult; new versions, new frameworks, new techniques. This feature gives you a head-start to our content, as it's being created. With Early Access you'll receive each chapter as it's written, and get regular updates throughout the product's development, as well as the final course as soon as it's ready.We created Early Access as a means of giving you the information you need, as soon as it's available. As we go through the process of developing a course, 99% of it can be ready but we can't publish until that last 1% falls in to place. Early Access helps to unlock the potential of our content early, to help you start your learning when you need it most. You not only get access to every chapter as it's delivered, edited, and updated, but you'll also get the finalized, DRM-free product to download in any format you want when it's published. As a member of Packt, you'll also be eligible for our exclusive offers, including a free course every day, and discounts on new and popular titles.