About the Dataset

This dataset contains Quality of Life indices for various countries around the globe, extracted from the Numbeo website. The data provides valuable metrics for comparing countries based on several aspects of living standards, which can assist in decisions such as choosing a place to live or analyzing global trends in quality of life.

OBS: The code to generate this dataset is presented on: https://www.kaggle.com/code/marcelobatalhah/web-scrapping-quality-of-life-index

Columns in the Dataset

1. Rank:
   The global rank of the country based on its Quality of Life Index according to Year (1 = highest quality of life).

2. Country:
   The name of the country.

3. Quality of Life Index:
   A composite index that evaluates the overall quality of life in a country by combining other indices, such as Safety, Purchasing Power, and Health Care.

4. Purchasing Power Index:
   Measures the relative purchasing power of the average consumer in a country compared to New York City (baseline = 100).

5. Safety Index:
   Indicates the safety level of a country. A higher score suggests a safer environment.

6. Health Care Index:
   Evaluates the quality and accessibility of healthcare in the country.

7. Cost of Living Index:
   Measures the relative cost of living in a country compared to New York City (baseline = 100).

8. Property Price to Income Ratio:
   Compares the affordability of real estate by dividing the average property price by the average income.

9. Traffic Commute Time Index:
   Reflects the average time spent commuting due to traffic.

10. Pollution Index:
    Rates the level of pollution in the country (air, water, etc.).

11. Climate Index:
    Rates the favorability of the climate in the country (higher = more favorable).

12. Year:
    Year when the metrics were extracted.

Key Insights from the Dataset

• The Quality of Life Index aggregates multiple indicators, making it a useful single metric to compare countries.
• Specific indices such as Safety Index or Health Care Index allow for focused analysis on areas like security or healthcare quality.
• Cost of Living Index and Purchasing Power Index can help determine the affordability of living in each country.

How the Data Was Collected

• The dataset was built using web scraping techniques in Python.
• The data was extracted from the "Quality of Life Rankings by Country" page on Numbeo.
• Libraries used:
  • requests for retrieving webpage content.
  • BeautifulSoup for parsing the HTML and extracting relevant information.
  • pandas for organizing and storing the data in a structured format.

Possible Applications

1. Relocation Decision Making:
   Use the dataset to compare countries and identify destinations with high quality of life, safety, and healthcare.

2. Global Analysis:
   Perform exploratory data analysis (EDA) to identify trends and correlations across quality of life metrics.

3. Visualization:
   Plot global maps, bar charts, or other visualizations to better understand the data.

4. Predictive Modeling:
   Use this dataset as a base for machine learning tasks, like predicting Quality of Life Index based on other metrics.

Luxembourg stands out as the European leader in quality of life for 2025, achieving a score of 220 on the Quality of Life Index. The Netherlands follows closely behind with 211 points, while Albania and Ukraine rank at the bottom with scores of 104 and 115 respectively. This index provides a thorough assessment of living conditions across Europe, reflecting various factors that shape the overall well-being of populations and extending beyond purely economic metrics. Understanding the quality of life index The quality of life index is a multifaceted measure that incorporates factors such as purchasing power, pollution levels, housing affordability, cost of living, safety, healthcare quality, traffic conditions, and climate, to measure the overall quality of life of a Country. Higher overall index scores indicate better living conditions. However, in subindexes such as pollution, cost of living, and traffic commute time, lower values correspond to improved quality of life. Challenges affecting life satisfaction Despite the fact that European countries register high levels of life quality by for example leading the ranking of happiest countries in the world, life satisfaction across the European Union has been on a downward trend since 2018. The EU's overall life satisfaction score dropped from 7.3 out of 10 in 2018 to 7.1 in 2022. This decline can be attributed to various factors, including the COVID-19 pandemic and economic challenges such as high inflation. Rising housing costs, in particular, have emerged as a critical concern, significantly affecting quality of life. This issue has played a central role in shaping voter priorities for the European Parliamentary Elections in 2024 and becoming one of the most pressing challenges for Europeans, profoundly influencing both daily experiences and long-term well-being.

Quality of Life Index (higher is better) is an estimation of overall quality of life by using an empirical formula which takes into account purchasing power index (higher is better), pollution index (lower is better), house price to income ratio (lower is better), cost of living index (lower is better), safety index (higher is better), health care index (higher is better), traffic commute time index (lower is better) and climate index (higher is better).

Current formula (written in Java programming language):

index.main = Math.max(0, 100 + purchasingPowerInclRentIndex / 2.5 - (housePriceToIncomeRatio * 1.0) - costOfLivingIndex / 10 + safetyIndex / 2.0 + healthIndex / 2.5 - trafficTimeIndex / 2.0 - pollutionIndex * 2.0 / 3.0 + climateIndex / 3.0);

For details how purchasing power (including rent) index, pollution index, property price to income ratios, cost of living index, safety index, climate index, health index and traffic index are calculated please look up their respective pages.

Formulas used in the past

Formula used between June 2017 and Decembar 2017

We decided to decrease weight from costOfLivingIndex in this formula:

index.main = Math.max(0, 100 + purchasingPowerInclRentIndex / 2.5 - (housePriceToIncomeRatio * 1.0) - costOfLivingIndex / 5 + safetyIndex / 2.0 + healthIndex / 2.5 - trafficTimeIndex / 2.0 - pollutionIndex * 2.0 / 3.0 + climateIndex / 3.0);

The World Happiness 2017, which ranks 155 countries by their happiness levels, was released at the United Nations at an event celebrating International Day of Happiness on March 20th. The report continues to gain global recognition as governments, organizations and civil society increasingly use happiness indicators to inform their policy-making decisions. Leading experts across fields – economics, psychology, survey analysis, national statistics, health, public policy and more – describe how measurements of well-being can be used effectively to assess the progress of nations. The reports review the state of happiness in the world today and show how the new science of happiness explains personal and national variations in happiness.

The scores are based on answers to the main life evaluation question asked in the poll. This question, known as the Cantril ladder, asks respondents to think of a ladder with the best possible life for them being a 10 and the worst possible life being a 0 and to rate their own current lives on that scale. The scores are from nationally representative samples for 2017 and use the Gallup weights to make the estimates representative. The columns following the happiness score estimate the extent to which each of six factors – economic production, social support, life expectancy, freedom, absence of corruption, and generosity – contribute to making life evaluations higher in each country than they are in Dystopia, a hypothetical country that has values equal to the world’s lowest national averages for each of the six factors. They have no impact on the total score reported for each country, but they do explain why some countries rank higher than others.

Quality of life index, link: https://www.numbeo.com/quality-of-life/indices_explained.jsp

Happiness store, link: https://www.kaggle.com/unsdsn/world-happiness/home

Quality of Life Indicators by Country

Overview

This dataset provides a detailed view of quality-of-life metrics for various countries, sourced from Numbeo. It includes indicators such as purchasing power, safety, health care, climate, cost of living, property prices, traffic, pollution, and overall quality of life. The data combines both numerical scores and descriptive categories to give a comprehensive understanding of these metrics.

Dataset Content

The dataset includes the following columns:

1. country: Name of the country.
2. Purchasing Power Value: Numeric score for purchasing power.
3. Purchasing Power Category: Qualitative category for purchasing power.
4. Safety Value: Numeric safety index score.
5. Safety Category: Qualitative safety category.
6. Health Care Value: Numeric score for health care quality.
7. Health Care Category: Qualitative health care category.
8. Climate Value: Numeric score for climate quality.
9. Climate Category: Qualitative climate category.
10. Cost of Living Value: Numeric score for cost of living.
11. Cost of Living Category: Qualitative cost of living category.
12. Property Price to Income Value: Numeric ratio of property price to income.
13. Property Price to Income Category: Qualitative property price-to-income category.
14. Traffic Commute Time Value: Numeric score for commute times.
15. Traffic Commute Time Category: Qualitative traffic commute category.
16. Pollution Value: Numeric pollution index score.
17. Pollution Category: Qualitative pollution category.
18. Quality of Life Value: Numeric score for overall quality of life.
19. Quality of Life Category: Qualitative quality of life category.

Source

The data from Numbeo, a global database providing cost of living, housing indicators, health care, traffic, crime, and pollution statistics for cities and countries.

Usage

This dataset can be used for: - Comparative analysis of quality-of-life indicators across countries. - Data visualization and storytelling for social, economic, or environmental trends. - Statistical modeling or machine learning projects on global living conditions.

Acknowledgments

The data was collected from Numbeo, which aggregates user-contributed data from individuals worldwide. Proper citation and credit to Numbeo are appreciated when using this dataset.

License

This data provided under Free Data Usage License by number. """

In 2023, Uruguay and Chile had the highest Digital Quality of Life index in Latin America and the Caribbean region, at **** and **** points on a scale from zero to one, respectively. In comparison, Venezuela and Honduras scored the lowest index among the presented countries. The index ranks the quality of digital wellbeing in a country.

As of 2024, South Africa and Morocco scored highest in the Digital Quality of Life index in Africa, with **** points each. Mauritius and Egypt followed closely with scores of **** points and **** points, respectively. African countries ranked significantly lower compared to other regions, with South Africa ranking 66th, while DR Congo came last in the 120th place.

According to the Digital Quality of Life Index, Singapore had the highest digital quality of life among countries in the Asia-Pacific region in 2023. In comparison, Cambodia scored the lowest among the assessed Asia-Pacific countries in 2023, reaching **** index points.

Quality of life is a measure of comfort, health, and happiness by a person or a group of people. Quality of life is determined by both material factors, such as income and housing, and broader considerations like health, education, and freedom. Each year, US & World News releases its “Best States to Live in” report, which ranks states on the quality of life each state provides its residents. In order to determine rankings, U.S. News & World Report considers a wide range of factors, including healthcare, education, economy, infrastructure, opportunity, fiscal stability, crime and corrections, and the natural environment. More information on these categories and what is measured in each can be found below:

Healthcare includes access, quality, and affordability of healthcare, as well as health measurements, such as obesity rates and rates of smoking. Education measures how well public schools perform in terms of testing and graduation rates, as well as tuition costs associated with higher education and college debt load. Economy looks at GDP growth, migration to the state, and new business. Infrastructure includes transportation availability, road quality, communications, and internet access. Opportunity includes poverty rates, cost of living, housing costs and gender and racial equality. Fiscal Stability considers the health of the government's finances, including how well the state balances its budget. Crime and Corrections ranks a state’s public safety and measures prison systems and their populations. Natural Environment looks at the quality of air and water and exposure to pollution.

Title: Top Cities Worldwide: Quality of Life Index 2024 Subtitle: Ranking the World's Best Cities for Living Based on Key Metrics

Source of Data: The dataset was collected from Numbeo.com, a publicly accessible database that provides data on various quality-of-life indicators across cities worldwide. Numbeo aggregates user-contributed data validated through statistical methods to ensure reliability.

Data Collection Method: Data was acquired through web scraping. Care was taken to follow ethical web scraping practices, adhering to Numbeo’s terms of service and respecting their robots.txt file.

Columns Description:

The dataset includes the following columns:

• Rank: City ranking based on the Quality of Life Index.
• City: Name of the city.
• Country: Country where the city is located.
• Quality of Life Index: Overall index measuring quality of life, calculated based on various sub-indices.
• Purchasing Power Index: Measures relative purchasing power in the city.
• Safety Index: Indicates how safe the city is based on crime rates.
• Health Care Index: Reflects the quality and accessibility of healthcare services.
• Cost of Living Index: Represents the cost of living, including housing, food, and transportation.
• Property Price to Income Ratio: A measure of housing affordability, calculated as the ratio of property prices to average incomes.
• Traffic Commute Time Index: Average time spent commuting within the city.

Limitations and Considerations:

• User-Generated Data: Since data on Numbeo is user-contributed, it may be subject to biases.
• Data Update Frequency: As Numbeo updates its data regularly, the dataset represents a snapshot in time and may require periodic updates.

Usage Note: The dataset is intended for research and analytical purposes. Users should verify the data's applicability for their specific use cases, considering the limitations mentioned above.

Geopolitical and economic shocks are destabilising living conditions globally. As instability intensifies, liveability scores for traditionally attractive cities are declining, while those for emerging cities are improving in education and infrastructure.

EIU’s Liveability Index ranks cities based on more than 30 indicators across five categories: stability, healthcare, culture and environment, education and infrastructure.

Each indicator is rated as acceptable, tolerable, uncomfortable, undesirable or intolerable. The ratings are then weighted to provide a score from 1 to 100.

The liveability rating of a city is given both as an overall score and as a score for each category. An overall position in the ranking of 173 cities is also provided.

The average for 2024 based on 138 countries was 5.56 points. The highest value was in Finland: 7.74 points and the lowest value was in Afghanistan: 1.72 points. The indicator is available from 2013 to 2024. Below is a chart for all countries where data are available.

The Social Progress Index ranks countries based on the well-being and quality of life of their citizens, considering factors such as access to education, healthcare, human rights, and environmental sustainability.

Data was initially taken from Numbeo as an aggregation of user voting.

• Quality of Life Index varies from 0 (bad quality) to 190 (top good quality)

This dataset is one of the public parts of City API project data. Need more? Try our full data

Estonia and Lithuania had the highest Digital Quality of Life index in Central and Eastern Europe in 2023, at **** and *** points on a scale from zero to one, respectively. In comparison, Bosnia and Herzegovina scored the lowest among the presented CEE countries. The index ranks the quality of digital wellbeing in a country.

The healthcare ranking reflects the quality of health care and access to health services in different countries. The assessment includes various factors such as life expectancy, access to medical services, healthcare funding, and technologies.

Poland received **** points for its internet security in 2023, ranking tenth by that indicator among 121 countries. The score for the electronic infrastructure was measured at **** points. In terms of the overall Digital Quality of Life Index score, the country ranked in the top five among Central and Eastern European (CEE) countries.

The dataset obtained consists of details of countries from year 2012-2023. The dataset consists of crime index, safety index, quality of life index, purchasing power index, cost of living index and unemployment rate in each country. Unemployment rate is based on age group 15+, 15-25+ and 25+ attributes.

The dataset is obtained by web scraping and the authenticity of data is not confirmed by the source.

Code used for web scraping: https://www.kaggle.com/code/mrudular/web-scraping-world-indices.

Data sources: 1. https://www.numbeo.com/cost-of-living/ 2. International Labour Organization. ILO modelled estimates database, ILOSTAT. https://ilostat.ilo.org/data/. Accessed 07-09-2023.

Quality of life varies significantly worldwide, influenced by factors like cost of living, healthcare, safety, and infrastructure. This case study analyzes Quality of Life Index rankings from 2022 and 2023 to identify trends, regional shifts, and key factors affecting global well-being.

🔍 What’s inside?

The 10 best and 10 worst ranked countries for both 2022 & 2023 Comparative analysis of ranking changes Visualizations: Bar charts, heatmaps, and Tableau maps for better insights Regional breakdowns to see if certain areas consistently rank high or low Key takeaways on what makes a country livable This project is designed to help analysts, travelers, and policymakers understand global quality-of-life trends.

📊 Tools Used: Excel, Google Sheets, Tableau, Python (optional for deeper analysis)

💡 Key Questions Explored:

Which countries improved or declined the most? Are there patterns in the best/worst-ranked regions? How do economic and social factors correlate with rankings?

Quality of Life Indicators: Rate by risk of poverty after social transfers (<60% of the median equivalised income) by geographical area. Annual. National.

Quality of Life Indicators: Population with lack of space in the dwelling by geographical area. Annual. National.