Accessibility of Python and Data Science



Python is the go-to language for most people when it comes to data science and is rapidly gaining popularity amongst introductory programming courses as well. The availability of the vast number of out-of-the-shelf libraries makes it relatively easy for data scientists to experiment with different data models. Similarly, its concise and indentation-based syntax is very clear and visually appealing to beginners, helping them to focus on the fundamentals rather than complex syntax.

However, are these benefits of Python and the plethora of tools around it available to everyone? Does its visual conciseness and elegance even appeal to those who cannot see? In this talk, we will discuss the experience of blind and visually impaired programmers and data scientists while using python. More specifically, the talk will focus on:

  • A brief look at what inclusiveness and accessibility means in the context of Python
  • Experience of blind and visually impaired programmers with varied programming experience
  • Accessibility of some of the popular Python libraries and tools for data science
  • The journey of data science modeling and the status of accessibility thereof from python point of view
    • Tools used for exploratory data analysis
    • Feature engineering
    • Model selection and training
    • Testing and metrics calculations
    • Deploying these models on the cloud
  • What we can do together to make Pythonic landscape more inclusive

Who is this talk for?

  • People who think everyone should be coding in python
  • People who think Python is very receptive and amenable as per needs
  • Enthusiasts looking to work on some challenging projects and make Python more inclusive
  • Pythonists contributing to different IDE

Outline of talk

  1. A quick primer on ideas of accessibility and inclusiveness (2-4 minutes)
  2. Summary of experiences of visually impaired persons while using python (4-5 minutes)
  3. Discussion on the accessibility of tools and libraries available for data science: pros and cons (8-10 minutes)
  4. Suggestions for areas where we can make an impact together (5-7 minutes)
  5. Q&A (5-6 minutes)

Key takeaways

  • An opportunity to understand how the blind and visually impaired code
  • An opportunity to work on projects that makes Python inclusive and accessible to everyone
  • A new perspective on designing inclusive interfaces


Here are some of the references which talk about experiences of visually impaired programmers in general and what can be done to improve it. Though this talk will be focusing on their experiences in python and data science.


  • An open mind
  • Basics of python

Content URLs:

Slides for PyCon talk

Speaker Info:

All the speakers are a member of I-STEM which is an organization working for equal opportunities for visually impaired persons in higher education and employment in STEM (science, technology, engineering, and mathematics) fields.

Rishabh Jain

Rishabh Jain is final year student of the integrated master's program in Applied Mathematics at IIT Roorkee. He leads the Data Science group at his college. His interests lie in data science especially in NLP, information retrieval and human-computer interaction.

Shakul Raj Sonker

Shakul Raj Sonker has graduated in 2019 in mathematics and computer science from Ashoka University. He is highly interested in data science, machine learning and AI. He has represented our country at international science seminar in Tokyo Japan. Shakul loves interacting with people and with this talk he is looking forward to interacting with many more.

Abhisar Waghmare

Abhisar, who is currently a 3rd year undergraduate student with his program focused in computer engineering is also a Co-Founder of I-STEM. He is a Python enthusiast with a demonstrated history of working in the research area. He is Skilled in c/c++ and Python etc. He also holds with him strong business developmental attributes helping him grow along with his organization.

Sunil Choudhary

Sunil is currently working in an investment bank. His interests include NLP, computer networking and finance. He loves to write hacks in python to make things accessible now and then.

Id: 1351
Section: Data Science, Machine Learning and AI
Type: Talks
Target Audience: Intermediate
Last Updated: