Dataset
africa-worldbank-inflation-consumer-prices-annual-fp-cpi-totl-zg
A Parquet file of annual inflation as measured by consumer prices for Africa, sourced from World Bank gender and regional statistics, indexed by Electric Sheep Africa for African data discovery and released in the 1K–10K row range.
Data preview
Dataset card
This dataset is a repackaged World Bank series on annual inflation (consumer prices, %) covering 52 African countries from 1960 to 2024, distributed as a parquet file on Hugging Face by Electric Sheep Africa under CC BY 4.0. It bundles 2,413 country-year observations into a single tabular format for macroeconomic analysis.
What this dataset contains
The file stores country-year observations of the World Bank indicator FP.CPI.TOTL.ZG, the headline annual percent change in consumer prices. Coverage spans 52 African countries across 1960–2024, yielding 2,413 rows in total. The dataset is released under CC BY 4.0 and is sized between one thousand and ten thousand records, sitting in the free-open band for redistribution. Source attribution is retained to the World Bank, with Electric Sheep Africa providing the engineering and metadata wrapper.
Structure and fields
Each row is keyed by an indicator identifier and a country identifier. The schema includes indicator_id (string), indicator_name (string), country_iso3 (string), country_name (string), year (int64), and value (float64, the annual inflation rate as a percentage). The dataset is split into train and test partitions totaling 2,413 rows, delivered in parquet with a tabular structure that maps cleanly to a pandas DataFrame.
How analysts use it
Analysts can join country_iso3 and year to other macroeconomic series to compare inflation trajectories across African markets, benchmark monetary policy outcomes, or backtest macro-aware allocation rules. The long time span supports time-series work such as trend decomposition, volatility regimes, or forecasting inflation paths. Because the publisher is the World Bank and licensing is permissive, derived indicators and charts can be redistributed with attribution for internal investment research.
Documentation & references 1
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