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The Applied Data Science Workshop

You're reading from The Applied Data Science Workshop Get started with the applications of data science and techniques to explore and assess data effectively

Product type Paperback

Published in Jul 2020

Publisher Packt

ISBN-13 9781800202504

Length 352 pages

Edition 2nd Edition

Languages

Python

Tools

Jupyter

Concepts

Data Science

Author (1):

Alex Galea

View More author details

Table of Contents (8) Chapters

Preface

Installing Libraries

1. Introduction to Jupyter Notebooks

2. Data Exploration with Jupyter FREE CHAPTER

3. Preparing Data for Predictive Modeling

4. Training Classification Models

5. Model Validation and Optimization

6. Web Scraping with Jupyter Notebooks

Appendix

Data Workflow with pandas

As we've seen time and time again in this book, pandas is an integral part of performing data science with Python and Jupyter Notebooks. DataFrames offer us a way to organize and store labeled data, but more importantly, pandas provides time-saving methods for transforming data. Examples we have seen in this book include dropping duplicates, mapping dictionaries to columns, applying functions over columns, and filling in missing values.

In the next exercise, we'll reload the raw tables that we pulled from Wikipedia, clean them up, and merge them together. This will result in a dataset that is suitable for analysis, which we'll use for a final exercise, where you'll have an opportunity to perform exploratory analysis and apply the modeling concepts that you learned about in earlier chapters.

Exercise 6.04: Processing Data for Analysis with pandas

In this exercise, we continue working on the country data that was pulled from Wikipedia...

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Authors (1)

Galea

Galea

Alex Galea has been professionally practicing data analytics since graduating with a masters degree in physics from the University of Guelph, Canada. He developed a keen interest in Python while researching quantum gases as part of his graduate studies. Alex is currently doing web data analytics, where Python continues to play a key role in his work. He is a frequent blogger about data-centric projects that involve Python and Jupyter Notebooks.

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