# Economic Data Lab — HakimX (three exploratory projects)

**Project status:** Web-based interactive visualizations and reproducible SQL/Power Query scripts completed as of 2026-10-13. **No native Power BI Desktop .pbix has been created or tested.** Import the Power Query files into Desktop to complete that additional deliverable.

## Source / scope

World Bank, *World Development Indicators*, series `IT.NET.USER.ZS` (individuals using the Internet, % of population) and `NY.GDP.PCAP.CD` (GDP per capita, current US$). This is a 150-row dated **2026-09-24** CSV snapshot retrieved from:
https://github.com/ChessShark1000/world-bank-internet-income-snapshot

Six economies: Brazil, Canada, China, Germany, India, United States; years 2000–2024.
The World Bank data are CC BY 4.0. Attribution: World Bank, World Development Indicators. Reuse subject to attribution and revised data caveat.
This republished snapshot is **not an official World Bank publication**. We have not freshly re-pulled the API in this archive.

Indicator metadata:
- https://data.worldbank.org/indicator/IT.NET.USER.ZS
- https://data.worldbank.org/indicator/NY.GDP.PCAP.CD
- https://datahelpdesk.worldbank.org/knowledgebase/articles/889392

## Three distinct analyses

1. **Digital adoption** — trend analysis, reference-year ranking and year-over-year changes.
2. **Income & connectivity** — income/adoption snapshot; GDP per capita on a logarithmic axis, six-country Pearson correlation shown purely as a descriptive statistic.
3. **Catch-up dynamics** — end minus start internet penetration in *percentage points*, grouped and ranked by country.

All analysis excludes missing pairs rather than imputing values. The six-country convenience sample is **not globally representative**. GDP per capita is in **current US dollars**; it is not real/inflation-adjusted GDP. Correlation does not imply causality.

## Use with SQLite

1. Download `/data/world-bank-6-country-2000-2024.csv`.
2. In a `sqlite3 portfolio.db` terminal, paste or run:
```text
.read schema.sql
.mode csv
.import --skip 1 world-bank-6-country-2000-2024.csv wdi_snapshot
SELECT COUNT(*) FROM wdi_snapshot; -- expect 150
.read 01_digital_adoption.sql
.read 02_income_connectivity.sql
.read 03_digital_catchup.sql
```
3. Compare results against the website charts. SQLite 3.25+ for window functions.

## Use with Power BI Desktop (Power Query)

1. Open Power BI Desktop > Transform Data > New Source > Blank Query > Advanced Editor.
2. Paste `WDI_Base.pq`; name the query `WDI_Base`. (Alternatively replace Web.Contents with a local CSV path.)
3. Create three more blank queries named `P01_DigitalAdoption`, `P02_IncomeConnectivity`, and `P03_DigitalCatchup`. Paste the corresponding `.pq` files.
4. Load the queries. Set `country` as categorical and `year` as whole number; use line charts, a scatter chart with `log10_gdp_pc`, and a bar chart on `gain_percentage_points`.
5. Check data types, missing observations, filter contexts and SQL/WB numbers. Save the completed report as `.pbix` yourself. No PBIX is provided by this repository.

## Method and authorship note

These case studies were developed as a skills-building portfolio with AI assistance and public, attributed data. Code and methods are visible. They demonstrate exploratory analysis; they should **not** be presented as professional production Power BI deployments or independent source data collection.

## Next research backlog

Atlas of Economic Complexity: https://atlas.hks.harvard.edu/data-downloads/
The Atlas publishes country/product international trade data and prescribes dataset-level citations. The World Economic Forum has different source structures, licenses and methodologies; neither Atlas nor WEF data is included in these three case studies.