Book Image

SQL for Data Analytics - Third Edition

By : Jun Shan, Matt Goldwasser, Upom Malik, Benjamin Johnston
Book Image

SQL for Data Analytics - Third Edition

By: Jun Shan, Matt Goldwasser, Upom Malik, Benjamin Johnston

Overview of this book

Every day, businesses operate around the clock, and a huge amount of data is generated at a rapid pace. This book helps you analyze this data and identify key patterns and behaviors that can help you and your business understand your customers at a deep, fundamental level. SQL for Data Analytics, Third Edition is a great way to get started with data analysis, showing how to effectively sort and process information from raw data, even without any prior experience. You will begin by learning how to form hypotheses and generate descriptive statistics that can provide key insights into your existing data. As you progress, you will learn how to write SQL queries to aggregate, calculate, and combine SQL data from sources outside of your current dataset. You will also discover how to work with advanced data types, like JSON. By exploring advanced techniques, such as geospatial analysis and text analysis, you will be able to understand your business at a deeper level. Finally, the book lets you in on the secret to getting information faster and more effectively by using advanced techniques like profiling and automation. By the end of this book, you will be proficient in the efficient application of SQL techniques in everyday business scenarios and looking at data with the critical eye of analytics professional.
Table of Contents (11 chapters)
9
9. Using SQL to Uncover the Truth: A Case Study

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...