Survivor Player Performance

100%

Survivor Player Performance

✓ Published0🌍 Public

Last edited Jan 31, 2023

Created on Jan 31, 2023

This example demonstrates how binned aggregation can be used to analyze the relationship between a contestant's age, finish placement, and gender across multiple seasons of the show. The visualization presents a table of raw summary data, listing each player's age, finish position, and gender, plotted as a collection of preformatted text elements. The code uses D3 v7 functions like `csvParse` to load the dataset, and `select`, `join`, and `text` to render the results. It fetches the CSV file asynchronously and initially shows a loading state before displaying the aggregated summary.

AI-generated description

Examples of various data transformation techniques, specifically binned aggregation.

MIT Licensed

Similar vizzes

Loading thumbnail…

All Survivor Contestants

This example displays all Survivor contestants as a JSON preview, showing raw data loaded from a CSV file. It uses D3 v7’s `csvParse` to parse the data and update the visualization via unidirectional data flow, with `setState` triggering a re-render. The state initially loads asynchronously, displaying “LOADING” until the fetch completes, then rendering the parsed objects. The code demonstrates a simple data-loading pattern with D3’s selection and data joins, though the visual output is minimal—just a textual representation of the dataset.

KKyle?

71% match

Loading thumbnail…

Player Data Scatter Plot

This scatter plot visualizes player data, showing age on the x-axis and matches played on the y-axis, with each point’s radius scaled to the player’s score. The data is loaded from a CSV file via `d3.csv`, and the visualization is rendered as an SVG using D3 v6. Axes are created with `axisLeft` and `axisBottom`, while `scaleLinear` and `scaleSqrt` map the data values. A categorical color scheme distinguishes score ranges, and axis labels are added as text elements.

Aaniteshterala2000

64% match

Loading thumbnail…

Assignment q2

This visualization displays a pie chart comparing average total scores by gender, computed from the StudentsPerformance 2.csv dataset. It uses D3 v7’s `d3.pie` and `d3.arc` to generate slices, with each gender’s average of math, reading, and writing scores aggregated via `d3.group` and `d3.mean`. The SVG rendering includes animated slice transitions through `transition.attrTween`, hover tooltips, and a legend, with a blue-red color scale distinguishing male and female results.

BBhargav Reddy

63% match

Loading thumbnail…

Data Visualization Short Presentation Task8

This example loads a CSV dataset and computes the average age of children per country, displaying the result as a JSON summary using D3’s `flatRollup` and `sum`. The code demonstrates asynchronous data fetching with `fetch`, parsing via `csvParse`, and type coercion of numeric fields. It uses D3 v7 for data aggregation and DOM updates, selecting a container to render the computed summary as preformatted text. The visualization highlights a simple data-processing pipeline without graphical charts, focusing on aggregation logic and state management.

Aanith462@gmail.com

63% match

Loading thumbnail…

WORK

The visualization displays average GAD-7 scores by employment status and reason for playing games, with each employment category further divided into gender-based sub-bars using a grouped bar chart. It shows the complete dataset without aggregation, rendering all 16 data points from the CSV file. The implementation uses d3.csv for data loading, scaleBand for both the primary and nested categorical scales, scaleOrdinal with explicit RGB color values for gender encoding, and scaleLinear for the y-axis. Axes are rendered with d3.axisLeft and d3.axisBottom, while SVG rectangles draw the bars.

GGeorgeVard

63% match

Loading thumbnail…

Stacked Bar Chart

This stacked bar chart visualizes the frequency of game-playing habits across different age groups, with each bar segment representing a specific frequency category. The data is loaded from a CSV file using d3-dsv, then processed with d3-array to compute totals and sorted in descending order. The chart uses d3-scale for positioning and color encoding, d3-shape to compute stacked positions, and d3-axis for the axes, with y-axis labels formatted using SI prefixes via d3-format. The visualization is rendered as SVG, displaying the full distribution of responses across all age cohorts.

JJdlv00

62% match

Loading thumbnail…

GAV Performance : Age vs Mark vs Attendance

This scatter plot maps student age against mark and attendance for the GAV department, with each point representing an individual course record from the provided CSV data. The visualization uses D3 v5 with SVG rendering, employing `scaleLinear` for the x-axis (Age) and `scaleBand` for the y-axis (Mark), while attendance values are encoded but not directly shown in the current rendering. The chart displays axes via `axisLeft` and `axisBottom`, with rectangular bars sized by age and positioned by mark. Data preprocessing converts age, attendance, and mark strings to numbers before rendering.

Ppillliarun79

62% match

Loading thumbnail…

visualization7D3.js

This multi-line chart displays the average first-semester grade by age at enrollment, with separate lines for male and female students. The visualization uses D3.js v7 to load the dataset via `d3.csv`, clean and aggregate the data with `d3.rollups` and `d3.mean`, and render the chart as an SVG. Points along each line include interactive tooltips showing gender, age, and average grade. Axes are generated with `d3.axisBottom` and `d3.axisLeft`, and a legend distinguishes the two gender groups.

GGanesh Gundekarla

62% match