Jan 11-12, 2018
08:30 - 16:30
Instructors: Katrin Tirok, Justin Pringle
Helpers: Atish Deoraj, Clinton Chrystal
Data Carpentry workshops are for any researcher who has data they want to analyze, and no prior computational experience is required. This hands-on workshop teaches basic concepts, skills and tools for working more effectively with data.
We will cover Data Organization in spreadsheets, Introduction to Python, Data Analysis and Visualisation in Python, Data Management with SQL and Developing post-workshop learning communities. Participants should bring their laptops and plan to participate actively. By the end of the workshop learners should be able to more effectively manage and analyze data and be able to apply the tools and approaches directly to their ongoing research.
For more information on what we teach and why, please see our paper "Best Practices for Scientific Computing".
Who: The course is aimed at graduate students and other researchers. You don't need to have any previous knowledge of the tools that will be presented at the workshop.
When: Jan 11-12, 2018. 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). They are also required to abide by Data Carpentry's Code of Conduct.
Accessibility: We are committed to making this workshop accessible to everybody. The workshop organisers have checked that:
Materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.
Contact: Please email firstname.lastname@example.org for more information.
Registration: Please sign up by completing this form.
Please be sure to complete these surveys before and after the workshop.
Day 1 - Thursday 11 Jan
Day 2 - Friday 12 Jan
|08:30||Ice Breaker/Introductions||08:30||Warm up|
|09:00||Data organisation in Spreadsheets||9:00||Data Management with SQL|
|10:50||Introduction to Python||10:50||Data Management with SQL|
|13:00||Data analysis and visualisation with Python||13:00||Data analysis and visualisation with Python|
|16:20||Wrap up||16:20||Wrap up|
We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.
To participate in a Data 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.
Python is a popular language for research computing, and great for general-purpose programming as well. Installing all of its research packages individually can be a bit difficult, so we recommend Anaconda, an all-in-one installer.
Regardless of how you choose to install it, please make sure you install Python version 3.x (e.g., 3.6 is fine).
bash Anaconda3-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 DownloadsThen, try again.
yesand press enter to approve the license. Press enter to approve the default location for the files. Type
yesand press enter to prepend Anaconda to your
PATH(this makes the Anaconda distribution the default Python).
SQL is a specialized programming language used with databases. We use a simple database engine called SQLite in our lessons.
The Data Carpentry Windows Installer installs SQLite for Windows. If you used the installer to configure nano, you don't need to run it again.
SQLite comes pre-installed on Mac OS X.
SQLite comes pre-installed on Linux.
If you installed Anaconda, it also has a copy of SQLite
without support to
Instructors will provide a workaround for it if needed.
To interact with SQLite data bases we will use the SQLite Manager add on for the Firefox web browser. If you don’t have Firefox installed, you need to install it first and then you will be able to add the plugin. You need to install the special Extended Support Release (ESR) of Firefox since the add on is not working with the new Firefox Quantum.
If you don’t already have Firefox ESR, download Firefox from the Firefox ESR download page. Install Firefox following the installer instructions. To install the SQLite Manager add on go to https://addons.mozilla.org/en-US/firefox/addon/sqlite-manager/ within Firefox. Click on ‘Add to Firefox’ and follow the instructions. Add SQLite Manager to the menu: Menu (the three horizontal lines near the top right corner of Firefox) -> Customize, then drag the SQLite Manager icon to one of the empty menu squares on the right
If you don’t already have Firefox ESR, download Firefox from the Firefox ESR download page. Install Firefox following the installer instructions. To install the SQLite Manager add on go to https://addons.mozilla.org/en-US/firefox/addon/sqlite-manager/ within Firefox. Click on ‘Add to Firefox’ and follow the instructions. After restart the SQLite Manager will be added ot the Tools menu.
If you don’t already have Firefox, download Firefox from the Firefox download page. Install Firefox following the installer instructions. To install the SQLite Manager add on go to https://addons.mozilla.org/en-US/firefox/addon/sqlite-manager/ within Firefox. Click on ‘Add to Firefox’ and follow the instructions. After restart the SQLite Manager will be added ot the Tools menu.