Los Angeles G. Riha Air Pollution and Income

100%

Los Angeles G. Riha Air Pollution and Income

✓ Published0🌍 Public

Last edited Dec 12, 2018

Created on Dec 8, 2018

Forked from Orange County G. Riha Air Pollution and Income

A scatterplot for the Los Angeles area compares PM2.5 air pollution levels (x-axis) against a user-selectable income or health attribute from a dataset of regional census tracts. Using D3 v5, the visualization loads a CSV and converts its string columns to numbers. Animated circles transition between positions when the user changes the y-axis variable through a dropdown menu. The chart relies on D3's `scaleLinear`, `extent`, `axisLeft`, and `axisBottom` APIs to render scales and axes.

AI-generated description

MIT Licensed

Similar vizzes

Loading thumbnail…

G. Riha Air Pollution and Income

This interactive scatterplot explores the relationship between air pollution levels (ds_pm_pred) and household income across Los Angeles County census tracts. Users select different variables for the x- and y-axes via dropdown menus, enabling comparisons between pollution, income, poverty, and health insurance metrics. The D3 v5 visualization uses SVG circles with animated transitions, scaling axes with d3.scaleLinear, and rendering tick marks and labels through d3.axisBottom and d3.axisLeft. Data is loaded from a CSV file containing county-level demographic and environmental measurements.

Ggarrettriha

94% match

Loading thumbnail…

#3 G. Riha Air Pollution and Income

This interactive scatter plot explores the relationship between PM2.5 air pollution levels and various socioeconomic indicators across Los Angeles County census tracts, using data from the provided CSV. Users select which income, poverty, or health insurance metric to display on the y-axis, while the x-axis remains fixed on particulate matter concentration. The visualization uses d3.scaleLinear for axes, d3.axisBottom and d3.axisLeft for gridlines, and transitions circles with staggered delays per data point. A dropdown menu built with D3’s selection API lets viewers swap variables, dynamically re-rendering the SVG.

Ggarrettriha

93% match

Loading thumbnail…

G. Riha LA Pollution Analysis

This interactive scatter plot from G. Riha analyzes pollution and income across Los Angeles census tracts, showing PM2.5 air pollution values along the x-axis and median household income on the y-axis via a dropdown menu to toggle other demographic variables. The visualization uses d3.csv to load the data, d3.scaleLinear for both axes, and d3.axisLeft and d3.axisBottom for rendering tick marks. Circles are appended as SVG elements with opacity, while d3.format applies concise tick labels, and a custom dropdown menu component handles user selection.

Ggarrettriha

93% match

Loading thumbnail…

#5 G. Riha Air Pollution and Income

This interactive scatter plot explores the relationship between PM2.5 air pollution levels and various socioeconomic indicators across Los Angeles, Orange County, and the San Francisco Bay Area. The visualization uses dropdown menus to let viewers switch which region and which income, health insurance, or poverty metric is displayed on the y-axis. Built with D3 v5, the plot uses `scaleLinear`, `axisLeft`, and `axisBottom` for axes, while a transition with a duration of 900 milliseconds and staggered delays animates each circle from the center to its final position. The SVG rendering uses semi-transparent teal circles.

Ggarrettriha

91% match

Loading thumbnail…

SF Bay Area G. Riha Air Pollution and Income

The scatterplot visualizes the correlation between PM2.5 air pollution levels and various socioeconomic attributes across census tracts in the San Francisco Bay Area and Los Angeles. Users select which attribute to display on the y-axis and which region to analyze via dropdown menus. The visualization uses D3.js (v5) to render an interactive scatterplot with animated transitions, where each circle represents a tract and its position is determined by the selected variables. The code leverages D3's `scaleLinear`, `axisLeft`, and `axisBottom` functions to construct the axes, while the `dropdownMenu` component manages user input. Data is loaded from a local CSV file containing median household income, family income, healthcare coverage, and poverty rates.

Ggarrettriha

88% match

Loading thumbnail…

#4 G. Riha Air Pollution and Income

An interactive scatter plot explores the relationship between air pollution (PM2.5 levels) and socioeconomic attributes—income, health insurance coverage, and poverty rates—across three California regions. Users select a region and an attribute from two dropdown menus to update the visualization. The D3 v5 code loads data from a CSV file, creates animated SVG circles, and updates scales and axes dynamically. The visualization uses `scaleLinear`, `axisLeft`, `axisBottom`, and custom `dropdownMenu` and `scatterPlot` modules, with a transition animating point positions over 900 milliseconds.

Ggarrettriha

87% match

Loading thumbnail…

#2 G. Riha Air Pollution and Income

This interactive scatter plot explores the relationship between PM2.5 air pollution levels and various socioeconomic indicators, such as median household income, poverty rate, and lack of health insurance coverage, using data from census tracts. Dropdown menus let the user select any column for the y-axis while the x-axis remains fixed on PM2.5 levels. The visualization, built with D3 v5, renders circles with a fade and scale-in transition. It uses `scaleLinear`, `extent`, and `axisBottom`/`axisLeft` to build the chart, with SVG as the rendering format and a `transition().duration(900).delay()` animation.

Ggarrettriha

87% match

Loading thumbnail…

Orange County G. Riha Air Pollution and Income

This interactive scatterplot explores relationships between air pollution (PM2.5) and four socioeconomic attributes—median household income, median family income, percent without healthcare, and percent below poverty line—across California regions. Users select attributes via dropdown menus built with a custom `dropdownMenu` module. The visualization uses D3 v5 scales (`scaleLinear`), axes (`axisLeft`, `axisBottom`), and animated circle transitions (`transition().duration(300).delay(...)`) rendered as SVG. Data comes from `data.csv`, showing geographic variation in pollution exposure across income and demographic conditions.

Ggarrettriha

86% match