Gist 274f90837389b882eaf3813de64dac5f

100%

Gist 274f90837389b882eaf3813de64dac5f

✓ Published0🌍 Public

Last edited Apr 8, 2016

Created on Apr 8, 2016

This example visualizes Airbnb listings in Los Angeles, mapping each property’s location and price point across the city. The code loads a CSV of listing data into a Pandas DataFrame, then uses Vue with WebGL rendering to display the geographic distribution of rentals. While the notebook includes initial data exploration with NumPy and Seaborn, the primary visualization relies on the WebGL framework to render the spatial layout, showing how listing prices and availability vary across neighborhoods without relying on traditional 2D charting libraries.

AI-generated description

Similar vizzes

Loading thumbnail…

Gist 6ce6b2a6ecda4579b64f

This visualization uses a Vue.js interface to display a list of city and state locations, likely from a dataset of place names. It shows a static, text-based table of these locations, with no visible map or chart. The code relies on standard DOM rendering through Vue’s template system, without additional data-viz libraries like D3 or Three.js. The rendering approach is a simple list, and the data source appears to be a CSV of location strings. No interactive or dynamic behavior is evident beyond the initial display.

CCaged

70% match

Loading thumbnail…

Airbnb Vienna

This scatter plot visualizes Airbnb listing prices across Vienna’s 23 boroughs, with each circle representing one apartment’s price on the x-axis and its borough on the y-axis. Using D3 v5, the code loads data from a CSV file and applies `scaleLinear` for both axes, `axisLeft` and `axisBottom` for tick marks, and SVG circles for data points. The chart’s opacity and teal fill create a density effect, while gridlines and axis labels clarify the price distribution per district.

VValentineAuer

68% match

Loading thumbnail…

A Map for New York Airbnb

This map visualizes the distribution of Airbnb room types across New York City, with each circle representing a listing and color encoding room type. Hovering reveals the price via tooltip. Built with the vega-lite-api, it reads CSV data from a GitHub gist and renders an interactive scatterplot using latitude and longitude fields. The visualization uses vega-lite’s markCircle, d3.csv for data loading, and vega-tooltip for hover interactions, with a custom config to adjust axis and label styling.

XXinting Yao

67% match

Loading thumbnail…

Fork of ICE-6 (airbnb)

This interactive scatter plot displays Airbnb listings based on distance to the city center and metro distance, with point color encoding species (Adelie, Gentoo, or other). Built with D3 v5, it loads CSV data and maps values to an SVG canvas using `scaleLinear`, `extent`, and `axisLeft`/`axisBottom` for axes. Each point uses `circle` elements with a fixed radius, while custom labels, tick styling, and explicit axis titles highlight the plot. The visualization emphasizes geographic proximity patterns against guest satisfaction metrics from the Airbnb dataset.

Pprathyusha-reddy-arch

67% match

Loading thumbnail…

AirBnb Data Visualized

This scatterplot displays the relationship between Airbnb listing prices and their reviews per month, with each circle representing a property. The visualization uses D3 v5 to load CSV data and render an SVG. It employs `scaleLinear` for both axes, `axisBottom` and `axisLeft` for tick marks, and appends circles with fixed radius to show the data points. The chart is titled "AirBnb Prices Vs Reviews Per month" and includes axis labels for clarity.

KKishore Thamilvanan

66% match

Loading thumbnail…

Gist 177f6c8fe1ef0050c1d0d9e490f6f6d5

This example visualizes the centroids of French communes as a particle system, with each point positioned by latitude and longitude from a CSV dataset. Using WebGL rendering within a Vue framework, the visualization employs a force simulation to spatialize the points, while geographic context is provided through a canvas-based path drawing approach. The underlying data includes commune names, INSEE codes, population, and coordinates, allowing the particles to reflect real administrative geography. The rendering leverages d3.forceSimulation for dynamic positioning and canvas getImageData for analyzing pixel density, creating a dense, interactive map-like scatter of population centers.

PPhilippe Rivière

66% match

Loading thumbnail…

Scatter Plot for New York Airbnb

This scatter plot visualizes New York Airbnb listings, showing the average price for different room types across neighbourhood groups. Each circle represents a room type within a neighbourhood, with circle size encoding the average number of reviews. The visualization is built using the vega-lite-api and d3.csv for data loading, rendered via vega-lite and vega. The data comes from a hosted CSV file, and the chart uses config.js to customize axis labels and typography for improved readability.

XXinting Yao

65% match

Loading thumbnail…

Fork of Project Data Science

This visualization, built with D3.js and the Vega-Lite API, combines a scatter plot and a bar chart to explore Hanoi real estate data. The scatter plot displays price per square meter against distance to a hospital, with point size encoding the number of bedrooms. A brushing interval selector on the x-axis filters the bar chart, while clicking a bar highlights a specific house type in both panels. The bar chart shows the count of each property type, with colors representing the categorical house types. The data is loaded from a remote CSV file, and the visual styling, including axis colors and guide fonts, is defined in a separate configuration module.

SStíofán ♔ Ó Conchubhair

65% match