What is Python?

Python is a popular general-purpose programming language that is great for working with research data. It is free and open-source with a huge community and support network. It is available on all major systems (Mac, Windows and Linux), and is also accessible via convenient 'Jupyter notebook' environments on the web. Python has a simpler syntax than a lot of other programming languages. As it is widely used, work done in Python is reproducible (allowing other users and agencies the ability to rerun and confirm analyses) and versatile (Python can connect and be used with a variety of applications).

Open-source software has been developed by a community of people and is made available in full for others to use, inspect, reuse and contribute to.

Jupyter notebook environments allow researchers and data scientists to write the steps of a reproducible analysis and interact with Python via the web browser. In this case, the Python environment may run locally or on a cloud server.

Syntax is the structure of language and symbols in a programming language.

What is it useful for?

As one of the most popular programming languages, Python is very versatile and can be used in a wide variety of research activities. Because it is so popular, there is an extensive collection of libraries made by others that can be used with Python to extend its capabilities. One example of a library is SciPy, a specialised set of Python-based tools for mathematics, science, and engineering.

Common examples of Python use for research are:

  • Data analysis and statistics
  • Text and data mining
  • Data visualisation
  • Web scraping
  • Image analysis
  • Machine learning and AI

A programming library is a collection of functions and files that allow the user to do tasks without having to code it themselves.

Web scraping is the practice of extracting data from websites.

Where can I get it?

Python is available free from the Python Software Foundation, or as part of the Anaconda Distribution. You can run Jupyter-style notebooks in the cloud with Google Colaboratory or Azure Notebooks..

Python workshops

Python events run regularly throughout the year and include the following workshops:

  • Introduction to Python
  • Image analysis in Python with SciPy and scikit-image
  • TensorFlow and Machine Learning (Uses Python and requires previous experience with Python)

Who can register for a workshop

Our workshops are open to all Monash University research and professional staff, and graduate research students (PhD and Masters by Research).

Registering for a workshop

Workshop registration is available through myDevelopment. This aligns with myPlan and training records for staff, and enables more streamlined processes for assigning credit towards the Monash Doctoral Program for Graduate Research students.

To browse our upcoming workshops, please see our Events page. Alternatively, staff and graduate research students can search for upcoming Data Fluency workshops on myDevelopment:

    • Log into myDevelopment from your myMonash portal.
    • Type "Data Fluency" or the software your are interested in (eg. "python") into the search box to find a list of available workshops.

Where else to find training

You can find more online training materials for this tool via the Library. Visit LinkedIn Learning or Safari to access a range of videos, eBooks and online courses, or try using Library Search to find other resources to help you master this tool.

If you're still not sure where to start, use the details below to get in touch with the Data Fluency community.

Find out more

For further information or advice come to the weekly drop-in session, join the community discussion on Slack, subscribe to our mailing list or email



Can be used for:
  • Collecting data
  • Preparing & cleaning data
  • Analysing data
  • Visualising data

View our workshop materials on GitHub