Data Analysis Project: Exploring Total Annual Deaths in Nigeria, from 1990 to 2019.

Photo from Anadolu Ajansi on AA.com.tr

This project explores worldwide statistics of deaths, thirty-three causes of these deaths, and the years of these deaths. It aims at analyzing the figures specifically from the country, Nigeria, within the time frame of 1990 to 2019.

As someone who had only worked on guided projects, this project was an opportunity to practice my skills on something on my own. So, as part of my documentation process, I’ll discuss the methods and skills I used for this project.

Methods

1. Data Gathering: The dataset used for this project was gotten from here. I downloaded the dataset as a CSV file.
2. Data Cleaning: While trying to make use of the dataset on SQL Server, I noticed that the word spacing would become a drawback in the long run, so I had to get rid of them, and also change all the words to lowercase.
3. Data Study and Manipulation: For this, I made use of SQL Server to analyze and generate inferences.
4. Data Visualization: I created a report on Power BI to show my insights.

Analyses and Insights

First, I looked at the global figures. Then, I filtered out every other country, excluding Nigeria.

I then tried to get some basic knowledge on a few causes of deaths, and the total number of deaths resulting from them in Nigeria. I checked that of meningitis, Alzheimer’s Disease, and executions (according to Amnesty International).

I summed up the total deaths by each of the thirty-three causes,

then created a temp table for proper viewing, and inserted these values into it.

From this temp table, I sought to answer a few questions such as:

1. What were the top 10 causes of the most deaths?

The top 10 causes were diarrheal diseases, malaria, lower respiratory infections, neonatal disorders, cardiovascular diseases, HIV/AIDS, tuberculosis, digestive diseases, neoplasms, and meningitis.

2. What was the sum of the total deaths altogether?

The sum of the total deaths was 43,692,695.

Then, I looked at the yearly distribution of deaths of the top 3 causes, which were: diarrheal diseases, malaria and lower respiratory infections.

From this, I found out that the highest count of deaths from diarrheal diseases was 297,403 from the year 1991; that of malaria was 280,604 from 2008; and that of lower respiratory infections was 216,774 from 2002.

Then, I created another temp table to view a sum of deaths by each year,

and inserted these sums into it.

From this, I answered the following questions:

3. What was the most number of deaths, and what was the year with the most number of deaths?

From this, we can see that the most number of deaths in a year was 1,580,894, and the year with this number was 2007.

4. What was the least number of deaths, and what was the year with the least number of deaths?

Again, from this, we can see that the least number of deaths was 1,169,882, and the year with this figure was 1990.

5. What was the average number of deaths per year?

The average number was 1,456,423.

Finally, to make sure that the sum of total deaths by cause and by year tally, I summed up the figures in each of the temp tables, and got the same number - 43,692,695.

Then, I headed on to Power BI for the visualization of my insights.

In this report, I visualized the total number of deaths & average number of deaths in Big Numbers; the top 6 causes of the most deaths in a pie chart; a line chart presenting the total deaths by year; and a bar chart presenting the total deaths by cause. Below, I wrote out my two major insights in a text box.

From this report, we can see that diarrheal diseases were the major cause of most deaths of Nigerians, especially children. If you’d like to read more on diarrheal diseases in Nigeria, you could go here.

Thanks for reading this. If you’d like to go through my code for this project, you could head on to my Github page here. You could also connect with me on Twitter and LinkedIn.

Bye!