Databases using SQL
OverviewTeaching: 60 min
Exercises: 5 minQuestions
What is a relational database and why should I use it?
What is SQL?Objectives
Understand the benefits of using a relational database
Set up a small database from csv files using SQLite
Understand SQLite data types
Note: this should have been done by participants before the start of the workshop.
We use DB Browser for SQLite and the
To start, let’s orient ourselves in our project workflow. Previously, we used Excel and OpenRefine to go from messy, human created data to cleaned, computer-readable data. Now we’re going to move to the next piece of the data workflow, using the computer to read in our data, and then use it for analysis and visualization.
The data we will be using is a time-series for the texts collected and encoded by the Text Creation Partnership. This is a real dataset.
First, let’s download and look at some of the cleaned spreadsheets
We’ll need the following four files:
Open each of these csv files and explore them. What information is contained in each file? Specifically, if I had the following research questions:
- How has the length and dates of Martin Luther title attributions changed over time?
- What is the average number of each titles, per year?
- What information can I learn about Martin Luther species in the 1500s, over time?
What would I need to answer these questions? Which files have the data I need? What operations would I need to perform if I were doing these analyses by hand?
In order to answer the questions described above, we’ll need to do the following basic data operations:
- select subsets of the data (rows and columns)
- group subsets of data
- do math and other calculations
- combine data across spreadsheets
In addition, we don’t want to do this manually! Instead of searching for the right pieces of data ourselves, or clicking between spreadsheets, or manually sorting columns, we want to make the computer do the work.
In particular, we want to use a tool where it’s easy to repeat our analysis in case our data changes. We also want to do all this searching without actually modifying our source data.
Putting our data into a relational database and using SQL will help us achieve these goals.
Definition: Relational Database
A relational database stores data in relations made up of records with fields. The relations are usually represented as tables; each record is usually shown as a row, and the fields as columns. In most cases, each record will have a unique identifier, called a key, which is stored as one of its fields. Records may also contain keys that refer to records in other tables, which enables us to combine information from two or more sources.
Why use relational databases
Using a relational database serves several purposes.
- It keeps your data separate from your analysis.
- This means there’s no risk of accidentally changing data when you analyze it.
- If we get new data we can just rerun the query.
- It’s fast, even for large amounts of data.
- It improves quality control of data entry (type constraints and use of forms in MS Access, Filemaker, Oracle Application Express etc.)
- The concepts of relational database querying are core to understanding how to do similar things using programming languages such as R or Python.
Database Management Systems
There are a number of different database management systems for working with relational data. We’re going to use SQLite today, but basically everything we teach you will apply to the other database systems as well (e.g. MySQL, PostgreSQL, MS Access, MS SQL Server, Oracle Database and Filemaker Pro). The only things that will differ are the details of exactly how to import and export data and the details of data types.
Let’s look at a pre-existing database, the
file from the Humanities dataset that we downloaded during
Setup. Clicking on the “open file” icon, then
find that file and clicking on it will open the database.
You can see the tables in the database by looking at the left hand side of the
screen under Tables, where each table corresponds to one of the
we were exploring earlier. To see the contents of any table, click on it, and
then click the “Browse and Search” tab in the right panel. This will
give us a view that we’re used to - just a copy of the table. Hopefully this
helps to show that a database is, in some sense, just a collection of tables,
where there’s some value in the tables that allows them to be connected to each
other (the “related” part of “relational database”).
The leftmost tab, “Structure”, provides some metadata about each table. It
describes the columns, often called fields. (The rows of a database table
are called records.) If you scroll down in the Structure view, you’ll
see a list of fields, their labels, and their data type. Each field contains
one variety or type of data, often numbers or text. You can see in the
dates table that most fields contain numbers (integers) while the
table is nearly all text.
The “Execute SQL” tab is blank now - this is where we’ll be typing our queries to retrieve information from the database tables.
- Relational databases store data in tables with fields (columns) and records (rows)
- Data in tables has types, and all values in a field have the same type (list of data types)
- Queries let us look up data or make calculations based on columns
- Every row-column combination contains a single atomic value, i.e., not containing parts we might want to work with separately.
- One field per type of information
- No redundant information
- Split into separate tables with one table per class of information
- Needs an identifier in common between tables – shared column - to reconnect (known as a foreign key).
Before we get started with writing our own queries, we’ll create our own
database. We’ll be creating this database from the three
we downloaded earlier. Close the currently open database and then
follow these instructions:
- Start a New Database
- New Database
- Give a name Save As. Creates the database in the opened folder
- Press Cancel
- Select File -> Import -> Table from CSV File.
- Select the
authors.csvfile to import
- Give the table a name that matches the file name (
authors), or use the default
- If the first row has column headings, check the appropriate box
- Make sure the delimiter and quotation options are appropriate for the CSV files.
- Press OK
- Import the
You can also use this same approach to append new data to an existing table.
Adding data to existing tables
- “File” tab -> Import -> Table from CSV file
- Enter data into a csv file and append
|CHARACTER(n)||Character string. Fixed-length n|
|VARCHAR(n) or CHARACTER VARYING(n)||Character string. Variable length. Maximum length n|
|BINARY(n)||Binary string. Fixed-length n|
|BOOLEAN||Stores TRUE or FALSE values|
|VARBINARY(n) or BINARY VARYING(n)||Binary string. Variable length. Maximum length n|
|INTEGER(p)||Integer numerical (no decimal).|
|SMALLINT||Integer numerical (no decimal).|
|INTEGER||Integer numerical (no decimal).|
|BIGINT||Integer numerical (no decimal).|
|DECIMAL(p,s)||Exact numerical, precision p, scale s.|
|NUMERIC(p,s)||Exact numerical, precision p, scale s. (Same as DECIMAL)|
|FLOAT(p)||Approximate numerical, mantissa precision p. A floating number in base 10 exponential notation.|
|DOUBLE PRECISION||Approximate numerical|
|DATE||Stores year, month, and day values|
|TIME||Stores hour, minute, and second values|
|TIMESTAMP||Stores year, month, day, hour, minute, and second values|
|INTERVAL||Composed of a number of integer fields, representing a period of time, depending on the type of interval|
|ARRAY||A set-length and ordered collection of elements|
|MULTISET||A variable-length and unordered collection of elements|
|XML||Stores XML data|
Different databases offer different choices for the data type definition.
The following table shows some of the common names of data types between the various database platforms:
|integer||Number (integer)||Int||Number||Int / Integer||Int / Integer|
|float||Number (single)||Float / Real||Number||Float||Numeric|
|string (variable)||Text (<256) / Memo (65k+)||Varchar||Varchar2||Varchar||Varchar|
|binary object OLE Object Memo Binary (fixed up to 8K)||Varbinary (<8K)||Image (<2GB) Long||Raw Blob||Text Binary||Varbinary|
SQL allows us to select and group subsets of data, do math and other calculations, and combine data.
A relational database is made up of tables which are related to each other by shared keys.
Different database management systems (DBMS) use slightly different vocabulary, but they are all based on the same ideas.