We extract time-series statistics, country profiles, and demographic indicators from Gapminder. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your schedule.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Global Indicators objects from gapminder.org. All fields typed and schema-versioned.
"indicator_id": "life_expectancy_years", "name": "Life expectancy", "category": "Health", "sub_category": "Mortality", "source_org": "Institute for Health Metrics and Evaluation", "updated_date": "2025-11-14", "metric_type": "float"
| # | indicator_id | name | category | sub_category | source_org | source_url |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Time-Series Data objects from gapminder.org. All fields typed and schema-versioned.
"country_code": "IND", "country_name": "India", "year": 2023, "indicator_id": "gdp_per_capita", "value": 7150.5, "unit": "USD", "projected_flag": false
| # | country_code | country_name | year | indicator_id | value | unit |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Country Profiles objects from gapminder.org. All fields typed and schema-versioned.
"country_code": "NGA", "name": "Nigeria", "region": "Sub-Saharan Africa", "income_group": "Level 2", "population": 223804632, "un_member": true, "iso3166_alpha3": "NGA"
| # | country_code | name | region | income_group | population | un_member |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Ignorance Quizzes objects from gapminder.org. All fields typed and schema-versioned.
"question_id": "q_pop_growth_01", "topic": "Population", "question_text": "How many children will there be in the year 2100?", "option_a": "2 billion", "option_b": "3 billion", "option_c": "4 billion", "correct_option": "option_a", "public_success_rate": 8.4
| # | question_id | topic | question_text | option_a | option_b | option_c |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Visualization Metadata objects from gapminder.org. All fields typed and schema-versioned.
"chart_id": "bubble_chart_main", "default_x_axis": "income_per_person", "default_y_axis": "life_expectancy", "default_color_scale": "world_4region", "time_range_start": 1800, "time_range_end": 2100, "animation_speed": 1.5
| # | chart_id | default_x_axis | default_y_axis | default_color_scale | default_size_axis | time_range_start |
|---|---|---|---|---|---|---|
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Gapminder curates thousands of metrics from multiple global entities. Our infrastructure handles the undocumented APIs, dynamic JSON payloads, and visualization data structures to deliver clean, queryable records.
Extract historical and projected data points across 195 countries and territories.
Capture definitions, source organizations, update frequencies, and methodological notes.
Scrape the full corpus of public misconceptions, quiz questions, and statistical realities.
Intercept and parse the underlying JSON blobs powering the interactive D3.js visualizations.
Track demographic shifts across the four income levels defined by Gapminder.
Join Gapminder metrics with ISO country codes for immediate warehouse integration.
Monitor for dataset revisions and new indicator releases on a weekly or monthly cadence.
Maintain data lineage by capturing the exact World Bank, UN, or NGO source for every metric.
Convert disparate CSV structures and API responses into a single, unified relational model.
Brief in. Clean data out.
Provide the specific indicators, regions, or datasets required. We design the extraction schema together.
We configure Playwright crawlers, API interceptors, and data coercion logic for gapminder.org.
Schema validation, null-rate checks, and data type coercion before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Gapminder relies heavily on client-side rendering and interactive data stores. We bypass the UI layer to extract the raw statistical payloads.
Gapminder interactive charts load data asynchronously. We intercept the XHR requests and WebSocket streams to capture the raw multi-dimensional arrays directly from the network layer.
We reverse-engineer the internal endpoints used by the Vizabi framework, extracting clean JSON before it hits the DOM and requires complex HTML parsing.
We handle paginated indicator lists with respectful concurrency, ensuring complete coverage without triggering firewall rules or overloading the non-profit servers.
Statistical data often mixes integers, floats, and nulls. Our pipeline enforces strict schema validation and type coercion before delivery to prevent warehouse ingestion errors.
We hash dataset versions. When Gapminder updates an indicator based on new UN reports, we emit only the modified rows, saving storage and compute on your end.
Integrate CO2 emissions, child mortality, and education metrics into corporate ESG models.
Correlate health outcomes with GDP per capita across decades to model emerging market growth.
Embed verified global statistics and misconception quizzes into ed-tech platforms and curricula.
Access clean, normalised time-series data for cross-sectional studies without manual data wrangling.
Power interactive news graphics and investigative reports with authoritative demographic trends.
Benchmark national performance against regional peers using standardised UN and World Bank derived indicators.
"Gapminder aggregates the world's most critical development metrics, but integrating their interactive datasets requires systematic extraction."
Relying on manual CSV downloads for thousands of indicators introduces human error and version control issues. DataFlirt automates the extraction of Gapminder's entire statistical corpus, handling API changes, schema normalisation, and delta updates. Your analysts get query-ready data, not download folders.
Everything supported by our gapminder.org scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and retry logic. Playwright executes JavaScript to trigger dynamic data loads and intercept API responses before they hit the DOM.
We map and monitor undocumented internal endpoints, extracting structured JSON directly from the network layer for maximum fidelity and speed.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About gapminder.org scraping, legality, and pipeline operations.
Ask us directly →Yes. Gapminder's statistical data is generally public domain or published under CC-BY licenses. We respect their terms, extract only public data, and use rate-limiting to avoid overloading their non-profit infrastructure.
We intercept the underlying JSON data feeds powering the D3.js and Vizabi components, bypassing the visual layer entirely to capture the raw multi-dimensional arrays.
Yes. We can filter the extraction pipeline by ISO country codes, regions, or income levels to limit warehouse storage and focus on your specific research area.
Gapminder updates indicators periodically based on source publications from the UN, World Bank, and NGOs. We typically run pipelines weekly or monthly to catch these revisions.
Absolutely. Every indicator record includes the original source organization, dataset name, and link where available, ensuring you maintain data lineage.
Our pipelines are monitored 24/7. If a DOM or API change breaks extraction, our engineers update the selectors and redeploy, usually within 24 hours.
20-minute scoping call. Pilot dataset within the week. Production within two. Stop downloading CSVs manually. Let DataFlirt deliver clean, normalised Gapminder statistics directly to your warehouse.
