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Practical Data Analysis Using Jupyter Notebook

You're reading from   Practical Data Analysis Using Jupyter Notebook Learn how to speak the language of data by extracting useful and actionable insights using Python

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Product type Paperback
Published in Jun 2020
Publisher Packt
ISBN-13 9781838826031
Length 322 pages
Edition 1st Edition
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Author (1):
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Marc Wintjen Marc Wintjen
Author Profile Icon Marc Wintjen
Marc Wintjen
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Table of Contents (18) Chapters Close

Preface 1. Section 1: Data Analysis Essentials
2. Fundamentals of Data Analysis FREE CHAPTER 3. Overview of Python and Installing Jupyter Notebook 4. Getting Started with NumPy 5. Creating Your First pandas DataFrame 6. Gathering and Loading Data in Python 7. Section 2: Solutions for Data Discovery
8. Visualizing and Working with Time Series Data 9. Exploring, Cleaning, Refining, and Blending Datasets 10. Understanding Joins, Relationships, and Aggregates 11. Plotting, Visualization, and Storytelling 12. Section 3: Working with Unstructured Big Data
13. Exploring Text Data and Unstructured Data 14. Practical Sentiment Analysis 15. Bringing It All Together 16. Works Cited
17. Other Books You May Enjoy
Gathering and Loading Data in Python

This chapter will explain what SQL isand why it is important for data analysis by teaching you how to use and access databases using SQLite for our examples. An overview of relational database technology will be provided along with insightful information on database systems to help to improve your data literacy when communicating with experts. You will also learn how to run SQLSELECTqueries from the Jupyter Notebook and how to load them into DataFrames. Basic statistics, data lineage, and metadata (data about data) will be explained using thepandaslibrary.

We will cover the following topics in this chapter:

  • Introduction to SQL and relational databases
  • From SQL to pandas DataFrames
  • Data about your data explained
  • The importance of data lineage
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