SQL & JavaScript & R

SQL scripts, JavaScript applications, and data analysis in R.

Why it matters

Data preparation, quality review, and statistical summaries make GIS workflows easier to inspect. These examples show those tasks across SQL, JavaScript, and R.

My contribution

The selected views show SQL data contracts and table-creation plans, JavaScript data-quality and parcel-planning interfaces, and R summaries and visualizations.

Result

The gallery shows schema checks, accepted and rejected synthetic features, parcel-planning assumptions, and grouped statistics and price distributions from the public diamonds dataset.

Tools

SQL
JavaScript
R
Shiny
ggplot2

SQL and JavaScript demonstrations use fictional data. The SQL plan is a preview, with no SQL executed. R views use public sample data. Full source files and datasets are not included.

Project gallery

Current SQL and JavaScript demonstrations use fictional data. R views use the public ggplot2 diamonds dataset. 6 images. Select an image to view it full size.

Light browser contract editor with fictional source and destination names, JSON settings, and a schema summary. — SQL data contract: source, destination, and field definitions. Fictional configuration.

Generated T-SQL plan with a schema summary and validation checks in the browser workspace; no execution or publication. — SQL table-creation plan with schema checks. Preview only; no SQL executed.

Standalone data-quality portal showing a dataset library, accepted and rejected feature counts, and an approval control with simulated roles. — JavaScript data-quality review: two accepted and four rejected synthetic features.

Standalone parcel scenario explorer with floor and coverage controls, two selected synthetic parcels, a map, and linked parcel rows. — JavaScript parcel planning: selected parcels and capacity assumptions. Synthetic geometry.

Diamonds Explorer summary with cut, color, clarity, and price filters, 53940 sample records, and grouped price statistics. — R Shiny: grouped statistics from the public ggplot2 diamonds dataset.

Diamonds Explorer Plot tab with five colored price boxplots grouped by cut and the current categorical and price filters. — R and ggplot2: comparing diamond price distributions by cut. Public sample data.

Technical details

Selected programming examples

Inspecting data definitions, quality decisions, planning assumptions, and statistical results.

Preview SQL data definitions and table-creation plans.
Review synthetic features and parcel-planning assumptions in JavaScript.
Summarize and visualize the public ggplot2 diamonds dataset in R.

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