KAUST Visualization Core Lab

13 October 2019

8:30 am - 5:00 pm

Instructors: David R. Pugh

Helpers: TBD

General Information

The Visualization Core Lab will host an Introduction to SQL for Data Science workshop. Visualization lab staff will provide an introduction to SQL for data science designed for learners with little or no previous experience with SQL programming.

Topics covered will include the following.

This hands-on lesson is part of the Introduction to Data Science Workshop Series being offered by the KAUST Research Computing Core Labs as part of our on-going efforts to build capacity in core data science skills at KAUST. The workshop curriculum largely follows the curriculum developed by Software Carpentry, a volunteer project dedicated to helping researchers get their work done in less time and with less pain by teaching them basic research computing skills.

This is a live-coding based workshop and learners are expected to bring their own laptops with the required software already downloaded and installed.

For more information on what Software Carpentry teaches and why, please see their paper "Best Practices for Scientific Computing".

Who: The course is aimed at graduate students (MSc and PhD), Post-docs, faculty and other research staff at KAUST. You don't need to have any previous knowledge of the tools that will be presented at the workshop.

Where: Auditorium 215 (between bldg. 2-3, level 0). Get directions with OpenStreetMap or Google Maps.

When: 13 October 2019. Add to your Google Calendar.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below).

Code of Conduct: Everyone who participates in Carpentries activities is required to conform to the Code of Conduct. This document also outlines how to report an incident if needed.

Contact: Please email help@vis.kaust.edu.sa for more information.


Surveys

Please be sure to complete these surveys before and after the workshop.

Pre-workshop Survey

Post-workshop Survey


Schedule

Before Pre-workshop survey
09:00 Introduction to SQL
10:30 Morning break
10:45 Combining Data
12:00 Lunch break
13:00 Creating and Modifying Data
14:30 Afternoon break
14:45 Programming with Databases
16:30 Wrap-up
17:00 END
After Post-workshop survey

We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.


Syllabus

Managing Data with SQL

  • Reading and Sorting Data
  • Filtering with where
  • Calculating New Values on the Fly
  • Handling Missing Values
  • Combining Values Using Aggregation
  • Combining Information From Multiple Tables Using join
  • Creating, Modifying, and Deleting Data
  • Programming with Databases
  • Reference...

Setup

To participate in a Software Carpentry workshop, you will need access to the software described below. In addition, you will need an up-to-date web browser.

We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.

The Bash Shell

Bash is a commonly-used shell that gives you the power to do simple tasks more quickly.

Video Tutorial
  1. Download the Git for Windows installer.
  2. Run the installer and follow the steps below:
    1. Click on "Next" four times (two times if you've previously installed Git). You don't need to change anything in the Information, location, components, and start menu screens.
    2. Select "Use the nano editor by default" and click on "Next".
    3. Keep "Use Git from the Windows Command Prompt" selected and click on "Next". If you forgot to do this programs that you need for the workshop will not work properly. If this happens rerun the installer and select the appropriate option.
    4. Click on "Next".
    5. Keep "Checkout Windows-style, commit Unix-style line endings" selected and click on "Next".
    6. Select "Use Windows' default console window" and click on "Next".
    7. Click on "Install".
    8. Click on "Finish".
  3. If your "HOME" environment variable is not set (or you don't know what this is):
    1. Open command prompt (Open Start Menu then type cmd and press [Enter])
    2. Type the following line into the command prompt window exactly as shown:

      setx HOME "%USERPROFILE%"

    3. Press [Enter], you should see SUCCESS: Specified value was saved.
    4. Quit command prompt by typing exit then pressing [Enter]

This will provide you with both Git and Bash in the Git Bash program.

The default shell in all versions of macOS is Bash, so no need to install anything. You access Bash from the Terminal (found in /Applications/Utilities). See the Git installation video tutorial for an example on how to open the Terminal. You may want to keep Terminal in your dock for this workshop.

The default shell is usually Bash, but if your machine is set up differently you can run it by opening a terminal and typing bash. There is no need to install anything.

Python (Optional)

Python is a popular language for research computing, and great for general-purpose programming as well. While there are many different ways to install Python, we recommend installing the 64-bit Python 3 version of Miniconda.

We will teach Python using the JupyterLab, a programming environment that runs in a web browser. For this to work you will need a reasonably up-to-date browser. The current versions of the Chrome, Safari and Firefox browsers are all supported.

  1. Open https://docs.conda.io/en/latest/miniconda.html with your web browser.
  2. Download the 64-bit Python 3 installer for Windows.
  3. Install Python 3 using all of the defaults for installation except make sure to check Add Anaconda to my PATH environment variable.
  1. Open https://docs.conda.io/en/latest/miniconda.html with your web browser.
  2. Download the 64-bit Python 3 installer for Linux. The installation requires using the shell. If you aren't comfortable doing the installation yourself stop here and request help at the workshop.
  3. Open a terminal window.
  4. Type
    bash Miniconda3-
    and then press Tab. The name of the file you just downloaded should appear. If it does not, navigate to the folder where you downloaded the file, for example with:
    cd ~/Downloads
    Then, try again.
  5. Press Return. You will follow the text-only prompts. To move through the text, press Spacebar. Type yes and press enter to approve the license. Press enter to approve the default location for the files. Type yes and press enter to prepend Miniconda to your PATH (this makes the Miniconda distribution the default Python).
  6. Close the terminal window.

R (Optional)

R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio.

Video Tutorial

Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE. Note that if you have separate user and admin accounts, you should run the installers as administrator (right-click on .exe file and select "Run as administrator" instead of double-clicking). Otherwise problems may occur later, for example when installing R packages.

You can download the binary files for your distribution from CRAN. Or you can use your package manager (e.g. for Debian/Ubuntu run sudo apt-get install r-base and for Fedora run sudo dnf install R). Also, please install the RStudio IDE.

SQLite

SQL is a specialized programming language used with databases. We use a simple database manager called SQLite in our lessons.

  • Run git-bash from the start menu
  • Copy the following curl https://kaust-vislab.github.io/2019-10-13-kaust-vislab/getsql.sh | bash
  • Paste it into the window that git bash opened. If you're unsure, ask an instructor for help
  • You should see something like 3.27.2 2019-02-25 16:06:06 ...

If you want to do this manually, download sqlite3, make a bin directory in the user's home directory, unzip sqlite3, move it into the bin directory, and then add the bin directory to the path.

SQLite comes pre-installed on macOS.

SQLite comes pre-installed on Linux.

  • In case of problems: register for an account at Python Anywhere
  • Download survey.db
  • Click on files and upload survey.db
  • Click on dashboard and Choose new console $ bash

If you installed Anaconda, it also has a copy of SQLite without support to readline. Instructors will provide a workaround for it if needed.