Section outline

  • Course Overview

    This course is a continuation of the Introduction to Python course.

    Learning Outcomes

    This course will help you to:

    1. Recap core elements such as functions, scripts, reading files from the Web using Python.
    2. Understand data extraction and visualisation techniques applied to social science research using Python.
    3. Make the right decisions dealing with and manipulating data taken from the web and API's using social science examples.

    • Course Instructors

      • Dr Rob Mastrodomenico

        Dr Rob Mastrodomenico obtained a BSc in Mathematics and Statistics and PhD in Statistics at the University of Reading. He has spent his career working as a data scientist in the sports sector, building predictive models for sporting events. In 2011 he set up Global Sports Statistics which provides consultancy and modelling services to clients in the sports sector. Aside from statistics, Rob’s other interest is in programming. He has years of experience in many different languages but has become an advocate for Python and all that it can do to support all aspects of dealing with and modelling data.

        View Bio for Dr Rob Mastrodomenico

      • Dr Phillip Brooker

        Dr Phillip Brooker is an interdisciplinary researcher in the field of social media analytics, with a background in sociology and sociological research methods (incorporating ethnomethodology, conversation analysis, science and technology studies, computer-supported cooperative work, and human-computer interaction). He has previously contributed to the development of Chorus (www.chorusanalytics.co.uk), a data collection and visual analysis package for social science research on Twitter. Phillip also co-convenes the Programming-as-Social-Science (PaSS) network (www.jiscmail.ac.uk/PaSS) which explores computer programming as a subject and methodological tool for social research and teaching. Phillip is currently employed as a Research Associate on CuRAtOR (Challenging Online Fear and Othering), which aims to investigate how online interactions result in 'cultures of fear'.

        View Bio for Dr Phillip Brooker

      • Course Resources

        You will need to access certain files and resources throughout the course to get the most out of the activities. You can find them all here. 

      • Video Transcripts

        You can access all video transcripts here. 

      • Pre-Course Self Assessment

        Before you dive into this course, spend a few moments reflecting on your familiarity with the topic and your current level of skills confidence. 

        You will then re-visit the same questions in our Post-Course Self Assessment and reflect on how the course has helped you develop in confidence and grow your skills. 

        • Module One: Overview

          This module covers:

          1. An introduction
          2. Installing Python
          3. Functions and scripts
          4. Reading from the web and files

        • Module Two: Manipulating Data

          This module covers:

          1. Pandas series
          2. Matplotlib series
          3. Pandas dataframes
          4. Matplotlib dataframes

        • Module Three: Extracting Data

          This module covers:

          1. Authentication
          2. Introduction to JSON
          3. Introduction to XML
          4. Web scraping using HTML
          5. Web scraping using Beautifulsoup4

        • Module Four: Practical Application

          This module covers:

          1. Planning a research task
          2. Three data analysis challenges

        • Post-Course Self Assessment

          Now you’ve completed the course, spend a few moments reflecting on where your familiarity with the topics and your confidence skills levels are at now. 

          Has the course helped you develop new skills and grow your confidence?

          You'll need to complete the Post-Course Self Assessment in order to download your certificate. If you didn't do the Pre-Course Self Assessment before starting the course, please go to the top of the page and reflect on your familiarity with the topic and your level of skills confidence before you started the course.

          • Completion: Certificate

            Completing all modules (plus the pre and post-course assessments) will unlock the course certificate, which you can then download here. Your course certificate will only be made available once you have completed all these sections.

            If you have difficulty accessing your certificate, please contact the Sage support team at: onlinesupport@sagepub.co.uk. You can also check out this FAQ page which may be helpful.

            • Give Feedback About This Course

              Did you enjoy the course? Please take two minutes to share your feedback. We use learner feedback in future course updates and developments to provide an excellent learning experience.

            • Accessibility

              We have high standards of accessibility on Sage Campus and as of May/June 2024 all activities within this course are keyboard and screen reader compatible. For more details on accessibility standards, please see the Sage Campus Accessibility Guide.

              For those using assistive technology, please note that within this course:

              • Tab components: JAWS and NVDA behave slightly differently. For NVDA to keep reading, it is best to exit focus mode and go back to browse mode. 
              • Matching: JAWS does not read out question label on dropdown focus.