Note: This assignment contributes 25% to your final SIT112 mark. It must be completed
individually and submitted to CloudDeakin before the due date: 5pm, 9 April 2020.
The theme for this assignment is to explore data related to Australia. In particular, we will use
a public dataset (provided by VicRoads for educational purposes), which provides information
on road traffic accidents at Victorian roads from 2000 until 2019. Our data strategy and task
specifications for this assignment will focus on the analysis and descriptive analytics of the
road traffic accidents.
1. Data and Resources
In the Assignment 1 folder, you will find the following files:
Filename Description
road_accidents_data_clean.csv The dataset file
field_description.pdf This file contains description for attributes in the data file
datadictionary_template.xlsx This is the template for the data dictionary file in Excel
assignment1_notebook.ipynb This is the Jupyter Notebook, which has been prepared
and pre-filled for you to complete the programming task
These are the files you will be required to work with for this assignment.
2. Task Description
There are two main tasks for this assignment:
• Construction of the data dictionary (35 marks) and
• Programming tasks to perform data analysis and descriptive analytics (65 marks).
2.1 Construction of the Data Dictionary (35 marks)
For a data scientist, after obtaining the dataset, the first most crucial task is to obtain a good
understanding of the data they are dealing with. This includes: examining the data attributes
SIT112 | Data Science Concepts
Lecturer: Dr Sergiy Shelyag
ASSIGNMENT ONE
Due: 5pm, Thursday 9 April 2020
(or, equivalently, data fields), seeing what they look like, what is the data type for each field,
and, from this information, determining suitable analysis tools. A systematic approach to this
process, as we have learned from the lectures and practical sessions, is to construct a data
dictionary for the dataset.
You are required to prepare two sheets in your data dictionary Excel file:
• Dataset description (5 marks)
• Attribute dictionary (30 marks)
The total for this task is 35 marks. The data description sheet is worth 5 marks. The attribute
dictionary is worth 30 marks, where each correct attribute specification is worth 2.5 marks.
Name your solution as [YourID]_datadictionary.xls and submit this file.
2.2 Programming task (65 marks)
A Python Jupyter Notebook file assignment1_notebook.ipynb has been prepared for you to
complete this task. Download this notebook, load it up to Jupyter and follow instructions inside
the notebook to complete this task.
The total for this task is 65 marks.
You are required to submit your solution in Jupyter Notebook format as well as its
exported version in html.
3. Summary for submission
This assignment is to be completed individually and submitted to CloudDeakin. By the due
date, you are required to submit the following files to the corresponding Assignment (Dropbox)
in CloudDeakin:
1. [YourID]_datadictionary.xls: your solution for the data dictionary for the given
dataset;
2. [YourID]_assignment1_solution.ipynb: your Jupyter Notebook solution source file;
3. [YourID]_assignment1_output.html: the output of your Jupyter Notebook solution
in html.
For example, if your student ID is: 123456, you will then need to submit three files:
• 123456_datatictionary.xls
• 123456_assignment1_solution.ipynb
• 123456_assignment1_output.html
END OF ASSIGNMENT DESCRIPTION