Summary and Schedule

In this lesson, you will learn the basics of data analysis and computational humanities using Python.

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.

What background knowledge do you need for this lesson?

  1. Basic mathematical background
  2. Familiarity with quantitative research methods
  3. Curiosity to learn about quantitative data analysis and Python programming

Datasets

In this lesson, we will work with multiple datasets. Each dataset represents a specific type of data that is suited to particular methods of quantitative analysis.

Links to be updated.

Data for Episode 2 (Analyzing Tabular Data): Artworks from MoMA

The metadata for artworks in the Museum of Modern Art (MoMA) collection can be downloaded from the museum’s GitHub Repository.

Since the data in this GitHub repository is continuously updated, we will be working with a version previously downloaded on April 9, 2025. This version is stored in the GitHub repository for this lesson, ensuring that the results you see during live coding match exactly what is demonstrated in the lesson.

To load the data from this lesson’s repository into your code, use the following URLs:

https://github.com/HERMES-DKZ/python_101_humanities/blob/main/episodes/data/moma_artworks.csv

Data for Episode 3 (Analyzing Text Data): Plays by Shakespeare and Marlowe

This dataset consists of the full texts of four plays by Christopher Marlowe and nine plays by William Shakespeare as follows. The Marlowe texts were downloaded from the website of Project Gutenberg. The Shakespeare texts stem from Folger Shakespeare Library. Each play has been saved to a .txt file.

Plays by Christopher Marlowe:

  • Doctor Faustus
  • Edward II
  • The Jew of Malta
  • The Massacre at Paris

Plays by William Shakespeare:

  • All’s Well That Ends Well
  • The Comedy of Errors
  • Hamlet
  • Julius Caesar
  • King Lear
  • Macbeth
  • Othello
  • Romeo and Juliet
  • The Winter’s Tale

You can download each set of works from the folders provided below:

https://github.com/HERMES-DKZ/python_101_humanities/blob/main/episodes/data/shakespeare

https://github.com/HERMES-DKZ/python_101_humanities/blob/main/episodes/data/marlowe

Software Setup

Python and Jupyter Notebook/Google Colab

To do the exercises in this lesson, you need an IDE (Integrated Development Environment). We recommend you use Jupyter Notebook or cloud-based equivalent such as Google Colab.

If you’re using Google Colab, you don’t need any installation. Just create a Google account - if you don’t have one already -, create a new Colab Notebook by clicking on New Notebook in the above link, and start coding.

Otherwise, to install Jupyter Notebook and Python on your computer together, we recommend using Anaconda. To do so, click on your operating system from the list below and follow the instructions.

  1. Open https://www.anaconda.com/download/success 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.

This video tutorial can help you with the installation.

  1. Open https://www.anaconda.com/download/success 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.

This video tutorial can help you with the installation.

  1. Open https://www.anaconda.com/download/success 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 (or Return) 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.

After installing Python and Anaconda, make sure to install the Python libraries that we are using in this lesson. If you haven’t installed Python libraries on your computer before, ask the instructors for support.