Property & Listing Data Wrangling and Dashboards

Overview

A set of small Python tools and standalone HTML dashboards for wrangling short-term-rental / property listing data. It converts nested listing and sales JSON into flat CSVs and visualizes markets and submarkets in self-contained HTML pages.

Why It Exists

Listing and market data arrives as deeply nested JSON that’s awkward to analyze in spreadsheets or BI tools. These scripts flatten that data into clean tabular CSVs and pair it with quick, dependency-free dashboards so non-technical stakeholders can explore listings, sales, and submarket trends.

What We Built

Python converters (convert_to_csv.py, convert_listings_to_csv.py, convert_sale_to_csv.py) that recursively flatten nested JSON objects, collapsing nested dicts into prefixed keys and joining arrays into delimited strings, to produce listings.csv, sale.csv, and submarkets2.csv. Alongside the converters are two standalone HTML dashboards (dashboard.html, submarkets-dashboard.html) for browsing the resulting data, plus the raw source text/JSON inputs. It’s an ad-hoc data-prep toolkit rather than a deployed application.

Technologies & Approach

Plain Python (standard library json/csv) for robust nested-JSON flattening, static HTML for zero-infrastructure dashboards, and a small shell helper for running conversions. The emphasis is on fast, reproducible data shaping with no heavyweight dependencies.

Outcome / Impact

The toolkit turned messy nested listing exports into analysis-ready CSVs and shareable dashboards quickly, exactly the kind of pragmatic data-prep that unblocks market analysis without standing up a full pipeline or BI stack.

Capabilities Demonstrated

• Recursive JSON flattening into analysis-ready tabular data
• Pragmatic, dependency-free data dashboards for non-technical users
• Fast ad-hoc data wrangling and market analysis tooling