Data Carpentry with Python

Netherlands eScience Center

Online

December 6 - 9, 2021

9:00 - 13:00 CET

Instructors: Leon Oostrum, Francesco Nattino, Sven van der Burg

Helpers: Ou Ku

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General Information

Data Carpentry develops and teaches workshops on the fundamental data skills needed to conduct research. Its target audience is researchers who have little to no prior computational experience, and its lessons are domain specific, building on learners' existing knowledge to enable them to quickly apply skills learned to their own research. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.

For more information on what we teach and why, please see our paper "Good Enough Practices for Scientific Computing".

Who: The course is aimed at graduate students and other researchers affiliated with Dutch research institutions. You don't need to have any previous knowledge of the tools that will be presented at the workshop.

Where: This training will take place online. The instructors will provide you with the information you will need to connect to this meeting.

When: December 6 - 9, 2021.

Requirements: Participants must have access to a computer 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).

Accessibility: We are dedicated to providing a positive and accessible learning environment for all. Please notify the instructors in advance of the workshop if you require any accommodations or if there is anything we can do to make this workshop more accessible to you.

Contact: Please email or training@esciencecenter.nl for more information.


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.


Syllabus

Data Organization in Spreadsheets

Data Cleaning with OpenRefine

Introduction to Python

Schedule

Day 1

Before starting Pre-workshop survey
09:00 Welcome & introduction
09:15 Data Organization in Spreadsheets
10:45 Coffee break
11:00 Data Organization in Spreadsheets (continued)
12:00 Coffee break
12:15 OpenRefine for Data Cleaning
12:45 Wrap-up
13:00 END

Day 2

09:00 Recap of Day 1
09:15 Introduction to Python
10:15 Coffee break
10:30 Introduction to Python (continued)
11:30 Coffee break
11:45 Introduction to Python (continued)
12:45 Wrap-up
13:00 END

Day 3

09:00 Recap of Day 2
09:15 Reading data from a file using Pandas
10:15 Coffee break
10:30 Extracting row and columns
11:30 Coffee break
11:45 Data Aggregation using Pandas
12:45 Wrap-up
13:00 END

Day 4

09:00 Recap of Day 3
09:15 Joining Pandas Dataframes
10:15 Coffee break
10:30 Data visualisation using Matplotlib
11:30 Coffee break
11:45 Data visualisation using Matplotlib (continued)
12:45 Wrap-up & Post-workshop survey
13:00 END

Setup

To participate in a Data Carpentry workshop, you will need access to software as 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.

Install the videoconferencing client

If you haven't used Zoom before, go to the official website to download and install the Zoom client for your computer.

Set up your workspace

Like other Carpentries workshops, you will be learning by "coding along" with the Instructors. To do this, you will need to have both the window for the tool you will be learning about (a terminal, RStudio, your web browser, etc..) and the window for the Zoom video conference client open. In order to see both at once, we recommend using one of the following set up options:

This blog post includes detailed information on how to set up your screen to follow along during the workshop.

Data

This workshop uses a tabular interview dataset from the SAFI Teaching Database and teaches data cleaning, management, analysis and visualization. We use a single dataset throughout the workshop to model the data management and analysis workflow that a researcher would use.

Clicking the this link will automatically download all of the files to your default download directory as a single compressed (.zip) file. To expand this file, double click the folder icon in your file navigator application (for Macs, this is the Finder application).

Spreadsheet program

OpenRefine

For this lesson you will need OpenRefine and a web browser. Note: this is a Java program that runs on your machine (not in the cloud). It runs inside a web browser, but no web connection is needed.

  1. Check that you have either the Firefox or the Chrome browser installed and set as your default browser. OpenRefine runs in your default browser. It will not run correctly in Internet Explorer.
  2. Download software from http://openrefine.org/
  3. Create a new directory called OpenRefine.
  4. Unzip the downloaded file into the OpenRefine directory by right-clicking and selecting "Extract ...".
  5. Go to your newly created OpenRefine directory.
  6. Launch OpenRefine by clicking openrefine.exe (this will launch a command prompt window, but you can ignore that - just wait for OpenRefine to open in the browser).
  7. If you are using a different browser, or if OpenRefine does not automatically open for you, point your browser at http://127.0.0.1:3333/ or http://localhost:3333 to use the program.
  1. Check that you have either the Firefox or the Chrome browser installed and set as your default browser. OpenRefine runs in your default browser. It may not run correctly in Safari.
  2. Download software from http://openrefine.org/.
  3. Create a new directory called OpenRefine.
  4. Unzip the downloaded file into the OpenRefine directory by double-clicking it.
  5. Go to your newly created OpenRefine directory.
  6. Launch OpenRefine by dragging the icon into the Applications folder.
  7. Use Ctrl-click/Open ... to launch it.
  8. If you are using a different browser, or if OpenRefine does not automatically open for you, point your browser at http://127.0.0.1:3333/ or http://localhost:3333 to use the program.
  1. Check that you have either the Firefox or the Chrome browser installed and set as your default browser. OpenRefine runs in your default browser.
  2. Download software from http://openrefine.org/.
  3. Make a directory called OpenRefine.
  4. Unzip the downloaded file into the OpenRefine directory.
  5. Go to your newly created OpenRefine directory.
  6. Launch OpenRefine by entering ./refine into the terminal within the OpenRefine directory.
  7. If you are using a different browser, or if OpenRefine does not automatically open for you, point your browser at http://127.0.0.1:3333/ or http://localhost:3333 to use the program.

Python

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., 3.9 is fine).

We will teach Python using Jupyter Lab, a programming environment that runs in a web browser (Jupyter Lab will be installed by Anaconda). 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 (some older browsers, including Internet Explorer version 9 and below, are not).

  1. Open https://www.anaconda.com/products/individual#download-section with your web browser.
  2. Download the Anaconda for Windows installer with Python 3. (If you are not sure which version to choose, you probably want the 64-bit Graphical Installer Anaconda3-...-Windows-x86_64.exe)
  3. Install Python 3 by running the Anaconda Installer, using all of the defaults for installation except make sure to check Add Anaconda to my PATH environment variable.

Video Tutorial

  1. Open https://www.anaconda.com/products/individual#download-section with your web browser.
  2. Download the Anaconda Installer with Python 3 for macOS (you can either use the Graphical or the Command Line Installer).
  3. Install Python 3 by running the Anaconda Installer using all of the defaults for installation.

Video Tutorial

  1. Open https://www.anaconda.com/products/individual#download-section with your web browser.
  2. Download the Anaconda Installer with Python 3 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 and navigate to the directory where the executable is downloaded (e.g., `cd ~/Downloads`).
  4. Type
    bash Anaconda3-
    and then press Tab to autocomplete the full file name. The name of file you just downloaded should appear.
  5. Press Enter (or Return depending on your keyboard). 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 (or Return) to approve the default location for the files. Type yes and press Enter (or Return) to prepend Anaconda to your PATH (this makes the Anaconda distribution the default Python).
  6. Close the terminal window.

To install the packages we’ll be using in the workshop, type the following in an Anaconda terminal:

conda install -y numpy pandas matplotlib jupyterlab seaborn

After installing Anaconda and the workshop packages, launch a Jupyter notebook by typing this command from the terminal:

jupyter lab

The notebook should open automatically in your browser. If it does not or you wish to use a different browser, open this link: http://localhost:8888.