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Background
In this assignment you will be required to undertake a preliminary data analysis on a dataset about Sustainable Energy and Environmental Impacts. The dataset provides comprehensive information on various aspects of energy consumption, environmental impact, and electricity access across different countries and regions. It is an invaluable resource for understanding global energy dynamics and environmental challenges. The primary objective is to analyse this data to draw insights that can guide decision-making in energy policy, environmental sustainability, and infrastructure development. You must present your results in a 5-minute video along with the presentation slides to be uploaded to Canvas. You must motivate your analysis as if it is solving a real business problem. You should also submit any Python code used to generate your visualisations.
Data Description
The dataset encompasses a range of variables from multiple countries over several years.
Key variables include:
· Access to clean fuels and technologies for cooking (percentage of population)
· Access to electricity (percentage of population)
· Renewable energy consumption (percentage of total final energy consumption)
· CO2 emissions and total greenhouse gas emissions (in kilotons of CO2 equivalent)
· Electricity access in rural and urban areas (percentage of respective populations)
· Time required to get electricity (in days)
· Renewable electricity output (percentage of total electricity output)
The data that must be used in this assignment can be downloaded here Download 在此处. A data dictionary is provided here Download 这里to help you with the assignment.
Analysis Streams
Students have the option to concentrate on one or more of the following areas. However, to achieve High Distinction marks, addressing all three areas is recommended:
1. Energy Consumption Analysis: Investigate patterns of energy consumption, focusing on access to clean fuels and renewable energy. This can reveal how different regions are progressing towards sustainable energy goals.
2. Environmental Impact Analysis: Examine the environmental footprint of various regions by analyzing CO2 and greenhouse gas emissions. This analysis can highlight the areas requiring urgent environmental policy interventions.
3. Electricity Access Analysis: Assess the electricity access disparity between rural and urban populations and the efficiency of electricity infrastructure development as indicated by the time required to get electricity.
Instructions
Instructions for uploading a video presentation are provided here. Your presentation should:
· Include at least three visualisations.
· Be no longer than 5 minutes.
· You must show your face during the presentation as well as the slides.
There are no other restrictions on your presentation. You do not need not use every variable or every observation in the dataset. It is likely that you will need to do some data cleaning and preparation using the concepts that we covered in Week 2. You may use any kinds of visualisation whether they be simple (e.g. bar charts) or complex (e.g. choropleths and interactive plots). See the rubric below for an indication of the marking criteria.
An important part of the assignment is showing that you can motivate your visualisations in a business setting. To do this, provide a context for your presentation to be delivered to multiple stakeholders (Government agencies, NGO, Policy makers, Energy industry leaders, etc.). The analysis should result in a clear understanding of the current state of global energy and environmental health. It should provide a foundation for developing strategies to address energy inefficiency, reduce environmental impacts, and improve electricity accessibility, especially in under-served regions. You may select any of the following objectives:
· To identify trends and disparities in energy consumption and environmental impact.
· To provide actionable insights for policy makers and stakeholders in energy and environmental sectors.
· To suggest areas where investment in renewable energy and infrastructure improvement is most needed.
To make the perspective of the assignment clear, you may choose to open your presentation with “I am XXX and I am a data scientist at Australian Department of Climate Change and Energy” or “I am XXX and work for a not-for profit organisation that helps with renewable energy transition targets”, etc.
PS. for Data Pre-Processing, you need a thorough examination and refinement of the dataset to ensure its readiness for in-depth analysis. This involves identifying and addressing any missing data through methods like imputation or exclusion, based on their impact on our analysis goals and the dataset's integrity. Additionally, you should scrutinize the dataset for errors and inconsistencies, such as mislabeled categories or implausible values, and implement corrections to mirror accurate real-world scenarios. A key part of pre-processing involves detecting outliers using visual tools to determine their influence on the analysis. Moreover, data transformation techniques, including normalization or scaling, may be applied to tailor the dataset for effective analysis and visualization.