Cost of Living - Country Rankings Dataset
The "Cost of Living - Country Rankings Dataset" provides comprehensive information on the cost of living in various countries around the world. Understanding the cost of living is crucial for individuals, businesses, and policymakers alike, as it impacts decisions related to travel, relocation, investment, and economic analysis. This dataset is intended to serve as a valuable resource for researchers, data analysts, and anyone interested in exploring and comparing the cost of living across different nations.
This dataset comprises four primary columns:
1. Countries: This column contains the names of various countries included in the dataset. Each country is identified by its official name.
2. Cost of Living: The "Cost of Living" column represents the cost of living index or score for each country. This index is typically calculated by considering various factors, such as housing, food, transportation, healthcare, and other essential expenses. A higher index value indicates a higher cost of living in that particular country, while a lower value suggests a more affordable cost of living.
3. 2017 Global Rank: This column provides the global ranking of each country's cost of living in the year 2017. The ranking is based on the cost of living index mentioned earlier. A lower rank indicates a lower cost of living relative to other countries, while a higher rank suggests a higher cost of living position.
4. Available Data: The "Available Data" column indicates whether or not data for a specific country and year is available.
This dataset is designed to support various data analysis and visualization tasks. Users can explore trends in the cost of living, identify countries with high or low cost of living, and analyze how rankings have changed over time. Researchers can use this dataset to conduct in-depth studies on the factors influencing the cost of living in different regions and the economic implications of such variations.
Please note that the dataset includes information for the year 2017, and users are encouraged to consider this when interpreting the data, as economic conditions and the cost of living may have changed since then. Additionally, this dataset aims to provide a snapshot of cost of living rankings for countries in 2017 and may not cover every country in the world.
Link: https://www.theglobaleconomy.com/rankings/cost_of_living_wb/
Disclaimer: The accuracy and completeness of the data provided in this dataset are subject to the source from which it was obtained. Users are advised to cross-reference this data with authoritative sources and exercise discretion when making decisions based on it. The dataset creator and Kaggle assume no responsibility for any actions taken based on the information provided herein.
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
This dataset provides insights into the cost of living and average monthly income across various countries and regions worldwide from 2000 to 2023. It includes critical economic indicators such as housing costs, taxes, healthcare, education, transportation expenses, and savings rates. The data is ideal for analyzing economic trends, regional comparisons, and financial planning.
Column Descriptions: Country: The name of the country where the data was recorded. Region: The geographical region to which the country belongs (e.g., Asia, Europe). Year: The year when the data was recorded. Average_Monthly_Income: The average monthly income of individuals in USD. Cost_of_Living: The average monthly cost of living in USD, including essentials like housing, food, and utilities. Housing_Cost_Percentage: The percentage of income spent on housing expenses. Tax_Rate: The average tax rate applied to individuals' income, expressed as a percentage. Savings_Percentage: The portion of income saved monthly, expressed as a percentage. Healthcare_Cost_Percentage: The percentage of income spent on healthcare services. Education_Cost_Percentage: The percentage of income allocated to educational expenses. Transportation_Cost_Percentage: The percentage of income spent on transportation costs.
By Andy Kriebel [source]
This dataset contains the average price of 1GB of mobile data by country. It includes data for over 150 countries, providing a valuable resource for anyone interested in global mobile data pricing trends. The data is sourced from Visual Capitalist, and was last updated in 2021
This dataset contains the average price of 1GB of mobile data by country as of April 2021. The data is sourced from Visual Capitalist.
To use this dataset, you can simply download it and then open it in your preferred spreadsheet software. The dataset is organized by rank, with the most expensive countries being listed first. Each row also lists the country's name and its corresponding average price for 1GB of mobile data.
If you want to compare the cost of mobile data across different countries, this dataset provides a useful starting point. You can also use it to track how prices have changed over time by comparing against previous editions of the dataset
1. To compare the cost of living in different countries.
2. To find out which countries have the most expensive mobile data plans.
**3. To see how the cost of mobile data has changed over time
License
License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.
File: Cost of 1GB of Data.csv | Column name | Description | |:---------------------------|:---------------------------------------------------------------------------| | Rank | The rank of the country based on the cost of 1GB of mobile data. (Numeric) | | Country | The country where the data was collected. (String) | | Avg Price of 1GB (USD) | The average price of 1GB of mobile data in the country, in USD. (Numeric) |
If you use this dataset in your research, please credit Andy Kriebel.
Movehub city ranking as published on http://www.movehub.com/city-rankings
Cities ranked by
Movehub Rating: A combination of all scores for an overall rating for a city or country.
Purchase Power: This compares the average cost of living with the average local wage.
Health Care: Compiled from how citizens feel about their access to healthcare, and its quality.
Pollution: Low is good. A score of how polluted people find a city, includes air, water and noise pollution.
Quality of Life: A balance of healthcare, pollution, purchase power, crime rate to give an overall quality of life score.
Crime Rating: Low is good. The lower the score the safer people feel in this city.
Unit: GBP
City
Cappuccino
Cinema
Wine
Gasoline
Avg Rent
Avg Disposable Income
Cities to countries as parsed from Wikipedia https://en.wikipedia.org/wiki/List_of_towns_and_cities_with_100,000_or_more_inhabitants/cityname:_A (A-Z)
http://www.movehub.com/city-rankings
https://en.wikipedia.org/wiki/List_of_towns_and_cities_with_100,000_or_more_inhabitants/cityname:_A
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Cost of Living - Country Rankings Dataset
The "Cost of Living - Country Rankings Dataset" provides comprehensive information on the cost of living in various countries around the world. Understanding the cost of living is crucial for individuals, businesses, and policymakers alike, as it impacts decisions related to travel, relocation, investment, and economic analysis. This dataset is intended to serve as a valuable resource for researchers, data analysts, and anyone interested in exploring and comparing the cost of living across different nations.
This dataset comprises four primary columns:
1. Countries: This column contains the names of various countries included in the dataset. Each country is identified by its official name.
2. Cost of Living: The "Cost of Living" column represents the cost of living index or score for each country. This index is typically calculated by considering various factors, such as housing, food, transportation, healthcare, and other essential expenses. A higher index value indicates a higher cost of living in that particular country, while a lower value suggests a more affordable cost of living.
3. 2017 Global Rank: This column provides the global ranking of each country's cost of living in the year 2017. The ranking is based on the cost of living index mentioned earlier. A lower rank indicates a lower cost of living relative to other countries, while a higher rank suggests a higher cost of living position.
4. Available Data: The "Available Data" column indicates whether or not data for a specific country and year is available.
This dataset is designed to support various data analysis and visualization tasks. Users can explore trends in the cost of living, identify countries with high or low cost of living, and analyze how rankings have changed over time. Researchers can use this dataset to conduct in-depth studies on the factors influencing the cost of living in different regions and the economic implications of such variations.
Please note that the dataset includes information for the year 2017, and users are encouraged to consider this when interpreting the data, as economic conditions and the cost of living may have changed since then. Additionally, this dataset aims to provide a snapshot of cost of living rankings for countries in 2017 and may not cover every country in the world.
Link: https://www.theglobaleconomy.com/rankings/cost_of_living_wb/
Disclaimer: The accuracy and completeness of the data provided in this dataset are subject to the source from which it was obtained. Users are advised to cross-reference this data with authoritative sources and exercise discretion when making decisions based on it. The dataset creator and Kaggle assume no responsibility for any actions taken based on the information provided herein.