Loading...
A longitudinal cross-national survey measuring social, political, moral, and religious values across European countries since 1981. Used in data engineering for social science research pipelines, cultural change analysis, and building time-series survey datasets for comparative European studies in Python.
EVS data is distributed via GESIS as SPSS or Stata files. Engineers use `pyreadstat.read_sav()` to load wave files, then merge across waves using respondent tracking variables for longitudinal panel analysis in pandas.
EVS provides rich survey microdata for training AI models that predict value orientations and societal attitudes from demographic features. Build RAG knowledge bases indexed on EVS findings to let LLMs answer questions about long-term shifts in European cultural values with academic survey evidence.
# pip install pyreadstat pandas
import pyreadstat, pandas as pd
# Download EVS SPSS file from GESIS: https://search.gesis.org/research_data/ZA7500
df, meta = pyreadstat.read_sav("ZA7500_v5-0-0.sav")
print(f"Rows: {len(df)}, Columns: {len(df.columns)}")
# Importance of religion by country
religion = df.groupby("country")["v6"].mean().sort_values()
print(religion.head(10))Official dataset source
More datasets used by Python data engineers.
Eurostat, the statistical office of the European Union, offers a comprehensive database of statistical data covering various domains such as economy, population, employment, environment and social issues.
The European Social Survey collects cross-national data on social attitudes, political engagement, values, and wellbeing through biennial surveys across 30+ European countries. Used in data engineering for longitudinal social science analysis, cross-national comparison pipelines, and building attitudinal trend dashboards in Python.
Data from the ninth round of the European Social Survey covering attitudes on health, climate change, democratic values, and social trust across 30+ European countries. Used in data engineering for longitudinal survey analysis, cross-national comparison pipelines, and social science research datasets in Python.