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The World Economic Forum publishes datasets and reports covering global competitiveness, gender parity, energy transition, and digital economy indicators across 140+ countries. Used in data engineering for economic research pipelines, policy benchmarking systems, and building global indicator dashboards in Python.
WEF datasets are downloadable as Excel/CSV from reports.weforum.org. Engineers use `pandas.read_excel()` with header row configuration to load multi-sheet competitiveness data, then reshape from wide to long format for trend analysis across countries and years.
WEF competitiveness and risk data informs AI strategic analysis tools. Build a RAG system indexed on WEF reports so LLMs can answer 'Which countries rank highest for digital infrastructure readiness?' or 'What does the WEF identify as the top global risks for 2025?' with authoritative sourcing.
# pip install pandas openpyxl
import pandas as pd
# Download GCI data from https://www.weforum.org/reports
df = pd.read_excel("WEF_GCI_4.0_2019_Dataset.xlsx",
sheet_name="Data", skiprows=2, engine="openpyxl")
print(df[["Economy", "Score"]].dropna().nlargest(10, "Score"))Official dataset source
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