README: update name of source XSLX, link to free text categorisation …

…ipynb

README.md

@@ -1,7 +1,7 @@
 ## Collaboration method for processing the survey data
 
 1. Clone this repo
-2. Download the latest spreadsheet from [sharepoint](<https://dmail.sharepoint.com/:f:/r/sites/SATRE/Shared%20Documents/WP1%20-%20Design/[wip](https://dmail.sharepoint.com/:f:/r/sites/SATRE/Shared%20Documents/WP1%20-%20Design/wip?csf=1&web=1&e=baCrJ9)?csf=1&web=1&e=baCrJ9>) and put it in the the local copy of the repo
+2. Download the spreadsheet `definitely-final-results-for-satre-tre-op-2023-05-16-1359.xlsx` from the private SATRE filestore and put it in the the local copy of the repo
 3. Build the conda environment
 4. Use `load_survey_data.load_data` to get a dataframe that can be easily used for further manipulations (see `summary-so-far.ipynb`)
 5. Run `pre-commit install` in the local copy of the repo to ensure the git hook for stripping notebook output is installed. Note that it operates on `git commit`, and removes all output from the local copy of the notebook
@@ -12,5 +12,5 @@ The original survey results contain sensitive data, but a sanitised version is a
 
 - [`data/public-results-for-satre-tre-op-2023-05-16-1359.csv`](data/public-results-for-satre-tre-op-2023-05-16-1359.csv) contains the ranked answers from the survey, along with:
   - manually categorised roles and institutions types
-  - extracted tokenised answers for some free text questions (e.g. software packages)
+  - extracted tokenised answers for some free text questions (e.g. software packages) using [`categorical_free_text.ipynb`](categorical_free_text.ipynb)
 - [`data/free-text-summaries.md`](data/free-text-summaries.md) contains a manual summary of the remaining collated free text answers