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Problem Background
Bellingen Riverwatch was created to provide consistent water quality data in the Bellinger and Kalang catchments following a disease
outbreak that caused a mass death event of the Critically Endangered Bellinger River Snapping Turtle (BRST) in early 2015. A lack of water
quality data was identified by scientists and community alike as a priority focus area.
Bellingen Riverwatch engages 43 local community volunteers and 5 schools to collect monthly water quality data at 30 sites every month
across the Bellinger, Never Never, and Kalang Rivers.
River health and water quality can change due to a wide range of factors, such as geology, rainfall, vegetation cover, gradient/steepness and
size of the catchment, human impacts through land use, natural disasters, climate, and much more. To help build a picture of a catchments’
health, ongoing and regular monitoring of water quality is required to build baseline data – a picture of the conditions for that particular
Submit Here (https://canvas.sydney.edu.au/courses/39595/assignments)
2022/4/28 00:31 Individual Assignment 1: BUSS6002 Data Science in Business
https://canvas.sydney.edu.au/courses/39595/pages/individual-assignment-1 2/3
The Bellingen Riverwatch citizen scientists have asked you to help answer the following question:
What were the water quality grades and scores for Bellingen Riverwatch sites annually and each summer?
To help answer the question you must perform an exploratory analysis of the data.
Your exploratory analysis must contain the following:

  1. A description of the dataset including a complete data dictionary
  2. Identification and categorisation of data quality issues
  3. Outline of any modifications or data processing accompanied by context driven justification
  4. Exploration of relationships and trends including both identification, analysis and any conclusions that can be drawn
    Throughout your analysis you must relate your findings to the context of the problem. For example when investigating data quality issues you
    will need to consider how the data has been collected and by who. Such information can be found in the Volunteer Manual.
    Your EDA will consist of a Jupyter Notebook, in which you will use Markdown cells to provide commentary on your EDA process
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