Road Accident Dashboard using Excel

Project Title - Road Accident Analysis

• This Repository offers a Comprehensive Analysis of Road Accident Data.
• By Leveraging this Project, we can unveil Valuable Insights and make Informed Decisions.

📃Description

Road Accidents ranks among the Foremost Global Causes of Injuries and Fatalities, presenting a critical area of Research dedicated to Traffic Accident Analysis and Predictive Techniques. By Scrutinizing the myriad factors that lead to these Tragic events, we aim to uncover the most Pivotal Contributors to Road Traffic Accidents.

Table of Content

• Project Goal
• Project Motivation
• Dataset
• Dataset Description
• Requirement
• Data Cleaning
• Installation : ETL Tools
• My Project
• Author
• Lessons Learnt
• Acknowledgement
• About Me
• Technical Skills
• Show your Support

🚀 Project Goal

To Develop an Intricate Road Accident Dashboard for the years 2021 and 2022, encapsulating Critical Insights and Data to Illuminate the key factors influencing Road Traffic Accidents.

Project Motivation

The Motivation driving this project is to Utilize Advanced Data Analysis and Predictive Techniques to significantly improve Road Safety and reduce the Incidence of Traffic Accidents Worldwide.

⏳ Dataset

The Road Accident Dataset is an Excel File, featuring one Comprehensive and Meticulously Detailed Sheet.

• Kindly Access and Download the Dataset via the Link provided below
• Link :- Raw Data.xlsx

📑 Dataset Description

When we examine the Data, we observe a number of Different Columns.

• Accident Index : An Unique Identifier for each Reported Accident.🚨
• Accident Date : The Date in which the Accident occurred.
• Day of Week : The Day in which the Accident occurred.
• Junction Details : Specifics about the Junction Location.⚠️
• Accident Severity : Degree of Impact or Harm caused by the Accident.🤕
• Latitude : Geographic Latitude of the Accident Location.
• Light Conditions : Lighting Status at the Time of the Accident.💥
• Local Authority (District) : Administrative District where the Accident Occurred.
• Carriageway Hazards : Obstacles or Dangers on the Road.
• Longitude : Geographic Longitude of the Accident Location.
• Number of Casualties : Total Number of Injured Individuals.🤕🤦‍♂️
• Number of Vehicles : Count of Vehicles Involved in the Accident.🚘
• Police Force : The Police Department responding to the Incident.🚓👮
• Road Surface Conditions : Quality and State of the Road Surface.
• Road Type : Classification of the Road.
• Speed Limit : Maximum allowable Speed at the Accident Location.⚠️☠️🚨
• Time : Exact Time when the Accident Occurred.
• Urban or Rural Area : Classification of the Area where the Accident Happened.
• Weather Conditions : Weather Conditions at the Time of the Accident.
• Vehicle Type : Classification of the Vehicles Involved.

Requirement

• ✅ The Total Casualties taken place after the Accident.
• ✅ Types of Casualites and its Percentage Distribution
• ✅ The total Casualties with respect to the Vehicle type.
• ✅ The Monthly trend showing Comparisons of Casualties for the Current Year and the Previous Year.
• ✅ Total Casualties by the Road Type.
• ✅ Distribution of total Casualties by the Road Surface.
• ✅ Total Casualties by Area and by Light Conditions.

🧹 Data Cleaning ✨

• Made Two new Columns 'Month' and 'Year' from 'Accident Date' column.
• Changed the Data Types wherever required.📅
• Removed Duplicates.
• Replaced data with meaningful data etc.📝

✅ Installation : ETL Tools ✅

Using the Raw Data, I crafted an Insightful and Visually Compelling Dashboard in Excel.

• MS Excel Installation Link :- https://www.microsoft.com/en-in/microsoft-365/excel

🚀 My Project

Comprehensive Analysis has been conducted on the Dataset, illustrated through a Variety of Engaging Plots📊📈.

Using Custom functions in PIVOT TABLE, I have manipulated data and created this Amazing Interactive Dashboard.

The Operations performed are:

• Applied Sorting and Filters📶
• Applied necessary Functions📊

Additionally, the Dashboard offers Customizable filters for Enhanced Data Exploration by Different Area 📍 and Accident Dates 📅🚑🚨.

This Illustrates the Analysis within Rural Areas 📍.

This Illustrates the Analysis within Urban Areas 📍.

This Illustrates the Analysis for the Accidents Date within 2021 Quarter1 📅.

This Illustrates the Analysis for the Accidents Date within 2022 Quarter3 📅.

This Illustrates the Analysis for the Accidents Date within 2022 Quarter4 📅.

Author 🙎‍♀️

• https://github.com/MansiPS

📝 Lessons Learnt

• ⭐Data Quality is Crucial
• ⭐Simplicity Enhances Usability
• ⭐Effective Use of Visuals
• ⭐Interactive Elements Add Value
• ⭐Consistent Formatting is Key
• ⭐Performance Optimization Matters

✍ Acknowledgement

Thank you to Kaggle for providing me this Invaluable Resource, which I leveraged to Enhance my Analysis and Visualization of the Data throughout the Project.

• Kaggle :- https://www.kaggle.com

🌟About Me 🙎‍♀️

I am Passionately delving into the realm of Data Analytics, engaging in thorough Learning and Hands-on Projects to refine my skills. As I explore Career Opportunities, I am eager to Transform data into Valuable Insights and contribute to a Dynamic and Innovative Organization.

Hi, I am Mansi! 👋

🔗Links

• 📌 LinkedIn :- https://www.linkedin.com/in/mansi-p-s-9052a0311
• 📌 Tableau :- https://public.tableau.com/app/profile/mansi.ps
• 📌 Github :- https://github.com/MansiPS

🛠 Technical Skills

🟡Scripting Language

Anaconda-Jupyter Notebook .

🟡Data Engineering

Exploratory Data Analysis 📊📈👨🏻‍💻.

🟡Microsoft

Excel , Word , Powerpoint .

🟡Data Visualization

Tableau , Power BI , Looker Studio .

🟡Libraries

Pandas, Numpy, Matplotlib, Seaborn, Plotly, Scipy.

✔️ Show your Support

If you appreciate this Project, please consider awarding it a ⭐

💥 Feedback

If you have any Feedback, please reach out to me at LinkedIn :- https://www.linkedin.com/in/mansi-p-s-9052a0311