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nltk_data
LA Questionnaire Analysis.ipynb
LA_all institutions_24.8.16.xlsx
README.md
requirements.txt

README.md

#Sample Jupyter notebook for analysis of open questions

##The anonymised data is drawn from a short survey of teaching and support staff and managers at three NZ tertiary institutions run in 2015/16

  • Click on LA Questionnaire Analysis.ipynb to launch the analysis notebook
  • When prompted, select Python 2 as the kernel
  • Wait for the notebook to load the go to the cell menu and choose run all
  • It takes a moment for the cells to execute.
  • Try changing the question number (In [3]). See variable openqs (In [1]) to see list of available questions. Go to cell menu and choose ‘run all below’. This executes the current cell and everything below it.
  • Try changing the myword variable to run a concordance (In [9]) for that word. Suggest choosing a word from the list of top 30 words in the response corpus.Again, you’ll need to go to cell menu and choose ‘run all below’ to see the changes in output.
  • Scroll down In [13] to see the concordance visualised as a Wordtree.

##There seem to be minor issues with Google Charts in notebook. The Google charts API is used for the Wordtree visualisation:

  • If Wordtree is not loaded, save any changes you have made, then refresh the entire page. Go to cell menu and choose run cells. The Wordtree should display.

  • If Wordtree still does not load and there is an error, click in In [13] and choose run cells from the cell menu. This just executes that cell.

  • Wordtree is from Google Chart.

  • You can click on any word to follow that branch.

  • Word weight reflects word frequency relative to keyword in context.