Udacity_DS_project_1

First project in my udacity-misk Data Science nano-degree: Blog post

Traffic accidents in Saudi Arabia have become one of the main problems the kingdom is dealing with. With this project I try to look at the number of children involved in those accidents and find out when and where their percentage is lower.

• What is the total number of accidents per month?
• What is the percentage of children that are involved in these accidents per month?
• What is the the percentage of children involved for each region during the whole year?
• Comparing the largest regions in the kingdom of Saudi Arabia, where is the highest percentage of children involvement into traffic accidents?

Files included:

• traffic-accident-statistics-as-of-1439-h.xls (data file in Excel format). It contains 17 sheets with the same number of columns and same headers. I have concatenated them to one dataframe in pandas.
  The data is provided by the Ministry of Interior - General Directorate of Traffic
  

• traffic_KSA.ipynb (Jupyter notebook using Python 3.8, and common libraries).
  

Installed modules to produce the jupyter notebook:

• pandas
• matplotlib
• numpy
• ploty
• plotly express
• seaborn

Acknoledgement:

The data I have used was sent to me from my mentor Mr. Haroon. I highly appreciate his help.
The data can be found on the Saudi portal for Open Data at:
https://data.gov.sa/Data/en/dataset/traffic-accident-statistics-as-of-1439-h

Key Steps for Project

Following the CRISP-DM process in finding solutions

1. I have used the traffic accidents data in KSA for the year 1439 Hijri calendar.

2. My business questions are:

   • What is the total number of accidents per month?
   • What is the percentage of children that are involved in these accidents per month?
   • What is the the percentage of children involved for each region during the whole year?
   • Comparing the largest regions in the kingdom of Saudi Arabia, where is the highest percentage of children involvement into traffic accidents?

3. I have created a Jupyter Notebook to explore and analyse the data:

   Preparing the data:

   • Read all sheets in the excel workbook and combine them.
   • Clean data, rename columns, and change the arabic naming of months to english words.
     
   • Create a dataframe for the data containing the age categories.
     
   • Provide visualized answers for my business questions

4. Please go to my blog post, where I present my insights:
   https://medium.com/@fatsammar/traffic-accidents-analysis-in-saudi-arabia-during-1939-hijri-df581248c1d4