Workshop series hosted by Pandas, NumFOCUS, and Iota
Weekly from Tuesday, February 6th to Tuesday, March 5th
13:00 - 15:00 Eastern Time (18:00 - 20:00 UTC)
Free and open to the public. Registration required. Seats may be limited. Recordings will be provided to all registrants.
Workshops will be hosted on Zoom. A Windows desktop or laptop is required. The NVDA screen reader will be used during the workshops.
This five-workshop series teaches the fundamentals of data analysis and sonification using nonvisual tools and technologies. The workshops are designed for those who are blind, low vision, or who otherwise have difficulty accessing visual tools for data science. The workshops cover some basics of the Python programming language, an introduction to the Pandas data science library, working interactively to explore data, preparing a data set for sonification, and using sonification to represent data. The workshop series uses the NVDA screen reader on Windows, and will be taught by blind / low vision practitioners. No prior experience with Python or data science is needed, but some familiarity with Windows and NVDA will be helpful.
Many introductions to data science focus on creating visual representations. However, while visualizations may initially seem essential when working with data, data is better thought of as inherently spatial rather than inherently visual. While visualizations such as maps and charts are the most common way to represent spatial representations, spatial relationships can also be represented in sound (sonification), feel (tactile graphics), or plain text (tables or natural language).
Outside of the focus on creating visualizations, tooling is also a major pain point for blind individuals who want to get started with data science. Common environments, such as Jupyter Notebooks, are not currently accessible using screen readers. This workshop series will primarily use a command line environment in conjunction with the NVDA screen reader. Participants will use the IPython interpreter for Python to access data science libraries such as Pandas and Astronify.
This series is generously supported by a small development grant provided by Pandas and NumFOCUS.
Sessions will be recorded and shared with all registrants after the event.
Participants at the Nonvisual Data Science Workshop Series will be expected to follow the NumFOCUS Code of Conduct.
| Date | Session | Description | Links |
|---|---|---|---|
| February 6th, 2024 | Nonvisual Python | This initial workshop will focus on accessing the command line environment and IPython with the NVDA screen reader. NVDA is chosen because it is a commonly used, free-of-cost and open source screen reader. The workshop will cover opening the terminal, accessing IPython, learning common Python types and objects, and using introspection functions. The workshop will culminate by importing pandas. | |
| February 13th, 2024 | Talking To Your Data: Querying Pandas DataFrames | In this workshop, participants will read a provided data set into a pandas DataFrame and learn how to query the data to answer questions. The workshop will cover pandas fundamentals such as Series and DataFrame objects, commonly used methods, accessing columns, and indexing. The workshop will emphasize returning results that are not overwhelming for screen reader users, focusing on methods that allow collapsing or limiting output. | |
| February 20th, 2024 | Manipulating Data | In this workshop, participants will learn how to prepare a data set for sonification. The workshop will cover common cleaning tasks such as renaming columns, creating derived columns, and changing dtypes. Participants will end by converting their data to an Astropy table for sonification. | |
| February 27th, 2024 | Sonification I: Principles of Sonification | This workshop will cover the fundamental principles of sonification, including the definition of sonification, existing use cases, the most common sonification methods, parameter mapping, and audifications. This workshop will also introduce the astronify library for sonifying astronomical data developed at Space Telescope Science Institute. | |
| March 5th, 2024 | Sonification II: Creating Sonifications with Astronify | The Astronify Python package is intended for the sonification of light curve data, a specific type of astronomical data that shows the observed brightness, or flux, of a star as a function of time. However, given that light curves are one-dimensional data, Astronify can be more broadly applied to sonify data that would be visualized as a line graph for sighted audiences. We will begin by sonifying recognizable data such as a simple linear function to familiarize the audience with data analysis and exploration via sonification. The data prepared in the previous modules can then be sonified and explored using Astronify. |
Pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, created as a library for the Python programming language. Read more
Iota is a consultancy that leverages connections between research and industry and the open source community to advocate, innovate, and inspire. Read more