100%

Fork of Penguins League of Legends

✓ Published0🌍 Public

Last edited Jan 24, 2024

Created on Jan 24, 2024

Forked from CSV Dataset Template - Penguins

This gallery example displays the League of Legends champion statistics dataset, revealing correlations between ban rates, win percentages, and roles such as TOP, MID, or JUNGLE. The visualization parses quantitative attributes like Score, Win %, and Ban % from CSV data, then renders a single champion’s summary as pretty-printed JSON text. The code uses D3.js to load and transform the data, with plain JavaScript template literals for output, highlighting specific entries like Caitlyn’s high pick rate and Irelia’s ban percentage.

AI-generated description

https://www.kaggle.com/datasets/vivovinco/league-of-legends-champion-stats

Is there a strong correlation between banned champions and win %? Role vs win %? Are there diamonds in the rough where the win % does not correlate with ban %? I'm guessing heat maps might be stronger in this data.

Challenge

Find 3 datasets on a topic you are interested in
For each of those, fork this viz and replace the data
Parse the quantitative attributes into numbers
Update README.md to indicate the original data source

MIT Licensed

Similar vizzes

Loading thumbnail…

Fork of Penguins Pokemon

This fork of the Penguins Pokemon visualization uses the Kaggle Pokemon dataset to explore whether legendary Pokemon have higher stats and how different stats correlate. The code loads data from a CSV file, parses quantitative attributes into numbers, and renders the first data entry as JSON in a preformatted block. It relies on the native JavaScript array parsing and template literals to display the data, with no external visualization libraries currently applied.

Bbenclark.3rd@gmail.com

66% match

Loading thumbnail…

Fork of HTML Starter

This visualization presents a grouped bar chart of Champions League team statistics, comparing goals scored, matches played, and wins for each team. The code loads a CSV dataset from a GitHub gist, aggregates the data using d3.rollup and d3.sum, and renders three colored bars per team using SVG rectangles. D3 v7 handles the scales, axes, and legend, with x-axis labels rotated for readability. The chart uses d3.scaleBand for categorical positioning and d3.scaleLinear for the numeric y-axis, providing a clear side-by-side comparison of these metrics.

BBALAJI MANDAVA

66% match

Loading thumbnail…

Fork of HTML Starter

This visualization displays bar charts for Champions League team statistics, comparing goals, matches played, and wins. It employs a group bar chart where each team’s metrics are shown side-by-side in steelblue, orange, and green bars. The D3.js library (v7) is used for data parsing, aggregation, and rendering to SVG, with scales and axes built using `d3.scaleBand`, `d3.scaleLinear`, and `d3.axisBottom`/`d3.axisLeft`. The data is fetched from a CSV URL and aggregated via `d3.rollup`. The SVG renders bars, axes, and a legend within an 800x600 canvas.

66264kusuma@gmail.com

65% match

Loading thumbnail…

Fork of Fork of Customizing Axes

This dashboard lets users explore player statistics from professional VALORANT matches through interactive bar and scatter plots. Using D3.js v4, it loads match data via `d3.csv` and renders SVG charts with animated transitions. Dropdown menus allow switching between metrics like KD, kills, and win rate for both visualizations. The scatter plot uses `d3.scaleLinear` for axes and `d3.scaleOrdinal` for point colors, while the bar chart sorts agents by the selected metric.

Ddaniel

65% match

Loading thumbnail…

VCtAxes

This example presents a two-panel visualization of Valorant Champions Tour player statistics from a CSV dataset. A horizontal bar chart compares performance metrics for different agents, while an animated scatter plot shows the correlation between selected metrics, such as kills, deaths, and assists. Interactive dropdown menus let users switch the metric displayed in the bar chart and choose which variables to plot on the scatter plot's X and Y axes. The visualization uses D3 v7 with ES6 modules, including `scaleLinear`, `scaleBand`, `axisLeft`, `axisBottom`, and `transition().duration()` for the animated circles.

Ddaniel

63% match

Loading thumbnail…

Fork of playing with json

This visualization displays cricket batting statistics from a T20 match between Sri Lanka and New Zealand. It uses D3.js v5 (including `d3.csv`, `d3.scaleLinear`, `d3.scaleBand`, `d3.axisLeft`, `d3.axisBottom`, `d3.schemePiYG`, and `d3.scaleSequential`) to render an SVG. Horizontal bars represent each batsman's innings, positioned by their first ball faced and colored by strike rate. Circles mark the last ball faced. The chart includes axis labels and text annotations for player names, runs, and strike rate. Data is loaded from a CSV file.

SshanLU999

62% match

Loading thumbnail…

Fork of Data Visualization Final Project-updated

This visualization explores Pokémon Go Great League data, showing type effectiveness in a color-coded table and a horizontal bar chart of Pokémon type distribution, with an input to filter top-ranked Pokémon. Users can select types and view scatter plots of fast and charge moves, where circle radius represents move popularity across Pokémon. The code uses D3 v5 APIs including `scaleBand`, `scaleOrdinal`, `scaleLinear`, `axisBottom`, `axisLeft`, and SVG rendering, with animations and interactive tooltips. Data comes from CSV files containing Pokémon stats, moves, and type matchups.

NNita

62% match

Loading thumbnail…

Fork of Fork of Customizing Axes

This example presents an interactive analysis of agent performance metrics from Valorant esports match data, displayed through a bar chart and scatter plot. Users can dynamically change the metric displayed on each chart using dropdown menus. The visualization is built with D3 v7, utilizing `scaleLinear` and `scaleBand` for the bar chart and `scaleLinear` with `extent` for the scatter plot. Data is loaded from a local CSV file and rendered as animated SVG circles and rectangles.

Ddaniel

62% match