Better Life Index OECD

Data Source & Purpose of Data Analysis

Data Source: Better Life Index

There is more to life than the cold numbers of GDP and economic statistics. This dataset contains the 2018 data of the Better Life Index which allows you to compare well-being across countries as well as measuring well-being, based on 11 topics the OECD has identified as essential, in the areas of material living conditions and quality of life.

OECD (2022), "Better Life Index", OECD Social and Welfare Statistics (database), https://doi.org/10.1787/data-00823-en (accessed on 08 October 2022).

Purpose of Data Analysis

1. Compare the Life Satisfaction Value by OECD countries
2. Find the Key Indicators(Topics) which show great differences between countries such as,
   • Labour Market Insecurity
   • Dwelling Without Basic Facilities
   • Feeling Safe Walking Alone At Night
3. Find the correlation between the Employment Rate Gender Gap and Life Satisfaction

Data Cleaning - Excel

• The columns without useful data or only with NULL data have been deleted.
• I cleared some column names as well, to keep them simple and meaningful.

For the brief data cleaning, Microsoft Excel has been used. The main process of data processing and cleaning was going to be done in SQL environment.

Data Cleaning and Aggregation - SQL

1. Created a table about Life Satisfaction of total population by country to inspect and compare with the Employment Rate Gender Gap
2. Reviewed the key indicators and ordered each data by Value
3. Created tables for each gender to inspect the individual Employment Rate and joined them to compare
4. Calculated the Gap of Employment Rate between genders and then compared this Value with Life Satisfaction to inspect the Correlation

/* Portfolio Project #1 Better Life Index OECD */
-- Total Life Satisfaction
CREATE TABLE TotalLifeSatisfaction
(
	Country nvarchar(255),
	LifeSatisfaction float
)
INSERT INTO TotalLifeSatisfaction
SELECT Country, Value
FROM BetterLifeIndexTrimmed
Where IndicatorCode = 'SW_LIFS' AND Inequality = 'Total'
Order by Country

-- Labour market insecurity Ranking
SELECT *
FROM BetterLifeIndexTrimmed
Where IndicatorCode = 'JE_LMIS' AND Inequality = 'Total'
order by Value

-- Dwelling without basic facilities Ranking
SELECT *
FROM BetterLifeIndexTrimmed
Where IndicatorCode = 'HO_BASE' AND Inequality = 'Total'
order by Value

-- Feeling safe walking alone at night
SELECT *
FROM BetterLifeIndexTrimmed
Where IndicatorCode = 'PS_FSAFEN' AND Inequality = 'Total'
order by Value desc

-- Correlation between Employment Rate Gender Gap and Total Life Satisfaction
-- Create Tables of Employment Rate for each gender
CREATE TABLE MenEmploymentRate
(
	Country nvarchar(255),
	IndicatorCode nvarchar(255),
	Indicator nvarchar(255),
	Unit nvarchar(255),
	MenValue float,
	Inequality nvarchar(255)
)
INSERT INTO MenEmploymentRate
SELECT Country, IndicatorCode, Indicator, Unit, Value, inequality
FROM BetterLifeIndexTrimmed
Where Inequality = 'Men'

CREATE TABLE WomenEmploymentRate
(
	Country nvarchar(255),
	IndicatorCode nvarchar(255),
	Indicator nvarchar(255),
	Unit nvarchar(255),
	WomenValue float,
	Inequality nvarchar(255)
)
INSERT INTO WomenEmploymentRate
SELECT Country, IndicatorCode, Indicator, Unit, Value, inequality
FROM BetterLifeIndexTrimmed
Where Inequality = 'Women'

-- JOIN TABLES and Calculate the Employment Rate Difference between the genders
CREATE TABLE GenderGapEmplTotalLifs
(
	Country nvarchar(255),
	IndicatorCode nvarchar(255),
	Indicator nvarchar(255),
	Unit nvarchar(255),
	MenValue float,
	WomenValue float,
	GenderGap float
)
INSERT INTO GenderGapEmplTotalLifs
SELECT m.Country, m.IndicatorCode, m.Indicator, m.Unit, m.MenValue, w.WomenValue,
CASE WHEN m.MenValue > w.WomenValue THEN m.MenValue - w.WomenValue
		ELSE w.WomenValue - m.MenValue
		END as GenderGap
FROM MenEmploymentRate m
JOIN WomenEmploymentRate w
	ON m.Country = w.Country
	AND m.IndicatorCode = w.IndicatorCode
Where m.IndicatorCode = 'JE_EMPL'
Order by IndicatorCode, Country

-- View the Correlation between GenderGap in Employment Rate and LifeSatisfaction by Countries
SELECT a.Country, a.GenderGap, b.LifeSatisfaction
FROM GenderGapEmplTotalLifs a
JOIN TotalLifeSatisfaction b
	ON a.Country = b.Country
									

Data Visualization

This dashboard consists of five data visualizations. At first, we have a bar chart about Life Satisfaction by countries. It shows the country rank about Life satisfaction. People in Finland have the highest life satisfaction, while people in South Africa and Turkiye have the lowest life satisfcation

The next bar chart below is about how much percentage of people live without basic facilities in each country. It says that over 30% of the population in South Africa is dwelling without basic facilities, while not even a single person has this problem in some countries. To make this insight taken easily, only the Top 5 and the Bottom 5 countries are kept in this visualization.

Labor Market insecurity was one of the key Indicators which tell us greatly different situations between countries. This bar chart was ordered by Value and kept only the Top 5 and the Bottom 5 countries as well.

The table below speaks about one of the key Indicators, Feeling Safe Walking Alone At Night. This table is showing directly the values instead of having a visualization. Because the contrast of 93%(Norway) and 40%(South Africa) is huge in the number form itself.

The final visualization is the plot chart about Employment Rate Gender Gap and Life satisfaction. It shows that the lower Employment Rate Gender gap a country has, the more likely is the country to have high Life Satisfaction.