Skip to main content
SimilarExport ZIP
100%

PROJECT

✓ Published0🌍 Public
MMonish Galla
Last edited Apr 25, 2024
Created on Apr 25, 2024
Forked from Hello VizHub

This heatmap visualizes salary data across job titles and company sizes, using a blue sequential color scale where darker shades indicate higher salaries in USD. Hovering over any cell displays a tooltip with the exact salary value. Built with D3.js v7, it renders SVG rectangles positioned by scaleBand axes, with a linear color scale and an axis-based legend showing the salary range. The visualization loads data from a merged JSON dataset containing job and salary information.

AI-generated description
MIT Licensed

Similar vizzes

Loading thumbnail…

Fork of Circles with D3

This visualization presents salary data as a heatmap, using color intensity on a linear scale from light gray to blue to represent salary amounts in US dollars across job titles and company sizes. The SVG chart employs D3 v7 with `scaleBand` for the categorical axes and `scaleLinear` for the color mapping. Hovering over individual rectangles triggers a tooltip displaying the exact salary value, while a legend with axis ticks and color rectangles provides a visual reference for the salary scale.

MMonish Galla
85% match
Loading thumbnail…

Project

This interactive visualization displays salary distributions by job title using an interactive bar chart. It uses D3.js (d3.v7) to load and process the data from a CSV file, grouping by job title and computing average salaries. A sidebar with range sliders, number inputs, and a dropdown menu allows users to filter by salary range and sort the bars by either salary or job title. The bars are rendered as SVG rectangles, with a hover effect that changes the fill color to highlight individual bars.

VVenkataSatyaRamKamini@my.unt.edu
82% match
Loading thumbnail…

8

This interactive dashboard visualizes data science job market trends from a Kaggle dataset, showing how average salaries vary by company size, job category, and experience level through dynamically updating bar charts. Users filter the data by job attributes and location, and the visualization redraws to reveal patterns such as larger companies paying higher salaries and senior roles commanding premium compensation. The interface uses D3.js v7 with SVG rendering, implementing interactive filters and tooltips to explore employment type distributions and geographical salary trends. The charts display salary data in both local currencies and USD across multiple years.

Hharisankarakeluth@my.unt.edu
80% match
Loading thumbnail…

PROJECT

The visualization presents a comparative analysis of data science salaries across the US and India, using four bar charts and histograms rendered as SVGs with D3 v6. It highlights the top highest-paying US job titles, the leading Indian companies by salary, and the salary distributions across different employment types and work models within the US market. The charts are generated using `d3.scaleBand` and `d3.scaleLinear` for axes, with data loaded from CSV files via `d3.csv`. Each chart applies a steelblue fill to bars and rotates x-axis labels for readability.

Bbrahmateja.edu2023@gmail.com
79% match
Loading thumbnail…

Project boxplot

This chart displays the average salary for different job titles, using bars with distinct colors and a legend to identify each category. Hovering over a bar reveals a tooltip with the exact job title and salary amount. The visualization is built with D3.js v7, using `d3.csv` to load data, `d3.rollup` and `d3.mean` for aggregation, `d3.scaleBand` and `d3.scaleLinear` for axes, and interactive mouseover events to control tooltip opacity. The SVG render includes rotated x-axis labels and a custom legend.

Mmalampatiramya03@gmail.com
79% match
Loading thumbnail…

12

This interactive bar chart visualizes average salaries across job titles in the data science field, using a Kaggle dataset with information on job categories, experience levels, company sizes, employment types, and locations. A dropdown menu system lets users filter by these attributes, and D3.js functions including `select`, `group`, and `mean` recalculate and redraw the bars dynamically. The SVG visualization sorts titles by descending salary, with tooltips and resize handling, and the code structure supports exploring salary variations by company size, experience, and job category.

Hharisankarakeluth@my.unt.edu
78% match
Loading thumbnail…

A7 HeatMap

This heatmap visualizes user demographics by profession and gender, with color intensity representing income levels. Built with D3.js v7 and React, it uses SVG rendering to display the grid of colored cells. The visualization includes a sequential blue color scale for income values, a gradient legend, and interactive tooltips showing detailed demographic information. The data is loaded from an external CSV file using d3.csv, with d3.autoType parsing the data. Axes are rendered using d3.axisBottom and d3.axisLeft, while d3.scaleBand positions the categorical variables.

SShazil Taqi
78% match
Loading thumbnail…

Project

This interactive choropleth map visualizes global data science salaries using a color gradient, with a World Atlas TopoJSON topology rendered via D3’s `geoMercator` projection and `geoPath`. Users filter salary ranges with two sliders that adjust the color scale domain, and hover tooltips display country-specific earnings. The map includes zoom functionality via `d3.zoom`, with salary data sourced from a CSV hosted on GitHub.

VVenkataSatyaRamKamini@my.unt.edu
78% match