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Jupyter for Data Science

You're reading from Jupyter for Data Science Exploratory analysis, statistical modeling, machine learning, and data visualization with Jupyter

Product type Paperback

Published in Oct 2017

Publisher Packt

ISBN-13 9781785880070

Length 242 pages

Edition 1st Edition

Languages

Python

Tools

Jupyter

Concepts

Data Analysis

Author (1):

Dan Toomey

View More author details

Table of Contents (11) Chapters

Preface

1. Jupyter and Data Science FREE CHAPTER

2. Working with Analytical Data on Jupyter

3. Data Visualization and Prediction

4. Data Mining and SQL Queries

5. R with Jupyter

6. Data Wrangling

7. Jupyter Dashboards

8. Statistical Modeling

9. Machine Learning Using Jupyter

10. Optimizing Jupyter Notebooks

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.

The rest of the chapter is locked

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Authors (1)

Toomey

Toomey

Dan Toomey has been developing application software for over 20 years. He has worked in a variety of industries and companies, in roles from sole contributor to VP/CTO-level. For the last few years, he has been contracting for companies in the eastern Massachusetts area. Dan has been contracting under Dan Toomey Software Corp. Dan has also written R for Data Science, Jupyter for Data Sciences, and the Jupyter Cookbook, all with Packt.

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