Reducing the number of high fatality accidents
📖 Background
You work for the road safety team within the department of transport and are looking into how they can reduce the number of major incidents. The safety team classes major incidents as fatal accidents involving 3+ casualties. They are trying to learn more about the characteristics of these major incidents so they can brainstorm interventions that could lower the number of deaths. They have asked for your assistance with answering a number of questions.
💾 The data
The reporting department have been collecting data on every accident that is reported. They've included this along with a lookup file for 2020's accidents.
Published by the department for transport. https://data.gov.uk/dataset/road-accidents-safety-data Contains public sector information licensed under the Open Government Licence v3.0.
import pandas as pd
accidents = pd.read_csv(r'./data/accident-data.csv')
accidents.head()
lookup = pd.read_csv(r'./data/road-safety-lookups.csv')
lookup.head()
💪 Competition challenge
Create a report that covers the following:
- What time of day and day of the week do most major incidents happen?
- Are there any patterns in the time of day/ day of the week when major incidents occur?
- What characteristics stand out in major incidents compared with other accidents?
- On what areas would you recommend the planning team focus their brainstorming efforts to reduce major incidents?
🧑⚖️ Judging criteria
CATEGORY | WEIGHTING | DETAILS |
---|---|---|
Recommendations | 35% |
|
Storytelling | 30% |
|
Visualizations | 25% |
|
Votes | 10% |
|
✅ Checklist before publishing into the competition
- Rename your workspace to make it descriptive of your work. N.B. you should leave the notebook name as notebook.ipynb.
- Remove redundant cells like the judging criteria so the workbook is focused on your story.
- Make sure the workbook reads well and explains how you found your insights.
- Check that all the cells run without error.
⌛️ Time is ticking. Good luck!