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README.md

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 license: apache-2.0
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+This dataset is a one-stop, meticulously curated resource designed for macroeconomists, data scientists, policy analysts, and business strategists. It bridges the gap between official macroeconomic statistics and real-world consumer expenses by combining real-time inflation data from the World Bank with crowd-sourced, granular cost-of-living indicators across all 194 recognized countries.
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+What does this dataset include?
+The dataset is structured to provide a 360-degree view of economic affordability. It is divided into three core layers:
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+Official Macroeconomic Data: Annual inflation rates (consumer prices, annual %) sourced directly from the World Bank API (indicator FP.CPI.TOTL.ZG), covering the latest available years (2020–2024), alongside country metadata including geographic region, income level (e.g., High-income, Lower-middle-income), and capital city coordinates.
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+Comparative Living Cost Indices: Standardized benchmark indices (relative to New York City = 100) that allow for easy cross-country comparison. These include the overall Cost of Living Index, Rent Index, Groceries Index, Restaurants Index, and the Purchasing Power Index.
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+Everyday Essential Goods & Services (in USD): To give a tangible sense of daily financial burden, the dataset includes average market prices for:
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+Food: Price of a 500g white loaf of bread.
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+Housing: Average monthly rent for a 1-bedroom apartment in the city center.
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+Transportation: Cost of a one-way local transport ticket and a standard monthly transport pass.
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+Utilities: Average monthly cost of basic utilities (electricity, heating, cooling, water, garbage) for a standard 85m² apartment.
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+Data Sources & Methodology:
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+Inflation & Country List: World Bank Open Data API (retrieved in real-time).
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+Cost Indices & Specific Prices: Aggregated from reputable international cost-of-living databases including Numbeo, Compare the Market AU analyses, Sputnik global surveys, and various national statistical offices.
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+Standardization: All monetary values are normalized and presented in US Dollars (USD) to ensure direct comparability across borders.
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+Potential Use Cases:
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+Machine learning models predicting inflation trends or housing affordability.
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+Exploratory data analysis (EDA) for academic papers on global economic disparity.
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+Dashboard creation for tracking "cost of living crises" or "purchasing power parity (PPP)" anomalies.
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+International relocation and expatriate compensation benchmarking.
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+Important Caveats (Read Me):
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+Time Variance: While the indices (Numbeo) represent a recent "point-in-time" snapshot, the World Bank inflation data is lagged by a few months (official annual releases). Users should treat the price data as indicative of the latest available period (2025–2026).
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+Data Availability: Not every country has complete reporting for every metric (especially small island nations or conflict zones). Missing values are left as NaN and clearly indicated in the data quality summary.
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+Crowd-sourced Nature: The price data (bread, rent, etc.) are averages derived from consumer contributions and may not perfectly represent rural versus urban extremes.
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+This dataset serves as a robust foundation for analyzing the global economic landscape, answering questions like "Where does my dollar go the furthest?" and "How does inflation impact everyday purchasing power?"
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