Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
SQL for Data Analytics

You're reading from   SQL for Data Analytics Harness the power of SQL to extract insights from data

Arrow left icon
Product type Paperback
Published in Aug 2022
Publisher Packt
ISBN-13 9781801812870
Length 540 pages
Edition 3rd Edition
Languages
Arrow right icon
Authors (4):
Arrow left icon
Benjamin Johnston Benjamin Johnston
Author Profile Icon Benjamin Johnston
Benjamin Johnston
Matt Goldwasser Matt Goldwasser
Author Profile Icon Matt Goldwasser
Matt Goldwasser
Jun Shan Jun Shan
Author Profile Icon Jun Shan
Jun Shan
Upom Malik Upom Malik
Author Profile Icon Upom Malik
Upom Malik
Arrow right icon
View More author details
Toc

Table of Contents (11) Chapters Close

Preface 1. Understanding and Describing Data 2. The Basics of SQL for Analytics FREE CHAPTER 3. SQL for Data Preparation 4. Aggregate Functions for Data Analysis 5. Window Functions for Data Analysis 6. Importing and Exporting Data 7. Analytics Using Complex Data Types 8. Performant SQL 9. Using SQL to Uncover the Truth: A Case Study Appendix

6. Importing and Exporting Data

Activity 6.01: Using an External Dataset to Discover Sales Trends

Solution:

  1. Before you can begin the rest of the analysis, you will need to properly load the dataset into Python and export it to your database. First, download the dataset from GitHub using the link provided: https://packt.link/l058E. If you are a Linux user, you can use the wget command like this:
    wget https://github.com/PacktPublishing/SQL-for-Data-Analytics-Third-Edition/blob/main/Datasets/public_transportation_statistics_by_zip_code.csv

Alternatively, you can navigate to the link via the browser. Once you navigate to the web page, click on Save Page As… using the menus on your browser:

Figure 6.31: Saving the public transportation .csv file

  1. Next, create a new Jupyter notebook. Launch Jupyter Notebook from Anaconda Navigator. In the browser window that pops up, create a new Python 3 notebook. In the first cell, type in the standard...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime