This repository uses the CITES Trade Dataset to create example SQL queries. These queries show how to perform all of the basic SQL operations. More advanced (or possibly intermediate) queries are performed in extra examples to explain how to perform certain tasks or to tell a specific story found within the data.

• SELECT
• DISTINCT
• WHERE
• ORDER BY
• NULL Values
• GROUP BY
• Aggregate Functions (MIN, MAX, SUM, etc.)
• INNER JOIN
• LEFT JOIN
• RIGHT JOIN
• OUTER JOIN
• UNION
• HAVING
• EXISTS
• CASE

The Falcons examples explore records which involve the Falco genus. Results can be directly piped into Matplotlib functions to plot different graphs to visually show SQL data.

• Extracting Data For Bar and Line Graphs
• Inner Joins
• Casting Values To Data Types

The Nations examples look at differences between European territories in the CITES table such as how much they import and export, as well as what species are popular. One single query is created at the end which collates all of the data explored.

• Creating and Dropping Tables
• Inserting Values Into Tables
• RANK() OVER() Function
• Subqueries
• The IN Operator

The Time Series examples look at several different time series problems in SQL, including:

• Moving Averages
• Running Totals
• Percentage Growth

The main data used in this repository relates to animal trades tracked by CITES, and can be obtained from the CITES website. This corresponds to the cites table in the database, which has been prefiltered to only include species in the class "Aves".

Supplementary data has been obtained from Leicestershire and Rutland Ornithology Society, and corresponds to the LeicestershireBirds table in the database.