Jupyter for Data Science by Toomey, Dan -- Read -- Imperial Library of Trantor

Index

Preface

What this book covers What you need for this book Who this book is for Conventions Reader feedback Customer support

Downloading the example code Errata Piracy Questions

Jupyter and Data Science

Jupyter concepts A first look at the Jupyter user interface

Detailing the Jupyter tabs What actions can I perform with Jupyter? What objects can Jupyter manipulate? Viewing the Jupyter project display

File menu Edit menu View menu Insert menu Cell menu Kernel menu Help menu Icon toolbar

How does it look when we execute scripts? Industry data science usage Real life examples

Finance, Python - European call option valuation Finance, Python - Monte Carlo pricing Gambling, R - betting analysis Insurance, R - non-life insurance pricing Consumer products, R - marketing effectiveness

Using Docker with Jupyter

Using a public Docker service Installing Docker on your machine

How to share notebooks with others

Can you email a notebook? Sharing a notebook on Google Drive Sharing on GitHub Store as HTML on a web server Install Jupyter on a web server

How can you secure a notebook?

Access control Malicious content

Summary

Working with Analytical Data on Jupyter

Data scraping with a Python notebook Using heavy-duty data processing functions in Jupyter

Using NumPy functions in Jupyter Using pandas in Jupyter

Use pandas to read text files in Jupyter Use pandas to read Excel files in Jupyter Using pandas to work with data frames

Using the groupby function in a data frame Manipulating columns in a data frame Calculating outliers in a data frame

Using SciPy in Jupyter

Using SciPy integration in Jupyter Using SciPy optimization in Jupyter Using SciPy interpolation in Jupyter Using SciPy Fourier Transforms in Jupyter Using SciPy linear algebra in Jupyter

Expanding on panda data frames in Jupyter

Sorting and filtering data frames in Jupyter/IPython

Filtering a data frame Sorting a data frame

Summary

Data Visualization and Prediction

Make a prediction using scikit-learn Make a prediction using R Interactive visualization Plotting using Plotly Creating a human density map Draw a histogram of social data Plotting 3D data Summary

Data Mining and SQL Queries

Special note for Windows installation Using Spark to analyze data Another MapReduce example Using SparkSession and SQL Combining datasets Loading JSON into Spark Using Spark pivot Summary

R with Jupyter

How to set up R for Jupyter R data analysis of the 2016 US election demographics Analyzing 2016 voter registration and voting Analyzing changes in college admissions Predicting airplane arrival time Summary

Data Wrangling

Reading a CSV file Reading another CSV file Manipulating data with dplyr

Converting a data frame to a dplyr table Getting a quick overview of the data value ranges

Sampling a dataset

Filtering rows in a data frame Adding a column to a data frame Obtaining a summary on a calculated field Piping data between functions Obtaining the 99% quantile Obtaining a summary on grouped data

Tidying up data with tidyr Summary

Jupyter Dashboards

Visualizing glyph ready data Publishing a notebook

Font markdown List markdown Heading markdown Table markdown Code markdown More markdown

Creating a Shiny dashboard

R application coding Publishing your dashboard

Building standalone dashboards Summary

Statistical Modeling

Converting JSON to CSV Evaluating Yelp reviews

Summary data Review spread Finding the top rated firms Finding the most rated firms Finding all ratings for a top rated firm Determining the correlation between ratings and number of reviews Building a model of reviews

Using Python to compare ratings Visualizing average ratings by cuisine Arbitrary search of ratings Determining relationships between number of ratings and ratings

Summary

Machine Learning Using Jupyter

Naive Bayes

Naive Bayes using R Naive Bayes using Python

Nearest neighbor estimator

Nearest neighbor using R Nearest neighbor using Python

Decision trees

Decision trees in R Decision trees in Python

Neural networks

Neural networks in R

Random forests

Random forests in R

Summary

Optimizing Jupyter Notebooks

Deploying notebooks

Deploying to JupyterHub

Installing JupyterHub Accessing a JupyterHub Installation

Jupyter hosting

Optimizing your script

Optimizing your Python scripts

Determining how long a script takes Using Python regular expressions Using Python string handling Minimizing loop operations Profiling your script

Optimizing your R scripts

Using microbenchmark to profile R script Modifying provided functionality Optimizing name lookup Optimizing data frame value extraction Changing R Implementation Changing algorithms

Monitoring Jupyter Caching your notebook Securing a notebook

Managing notebook authorization Securing notebook content

Scaling Jupyter Notebooks Sharing Jupyter Notebooks

Sharing Jupyter Notebook on a notebook server Sharing encrypted Jupyter Notebook on a notebook server Sharing notebook on a web server Sharing notebook on Docker

Converting a notebook Versioning a notebook Summary

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