final_data

final_data

This example previews the first row of a cleaned and geocoded World Cup cricket dataset. It displays the data as a formatted JSON object within an HTML `<pre>` tag, showing fields such as the city, its coordinates, the two competing teams, the over number, runs scored in that over, the winning details, and the full match description. The visualization uses the JavaScript `index.js` file to import the `merged_data.csv` file, convert string values for over number, runs, and coordinates to numeric types, and then render the entire record. This approach provides a static, text-based view of the raw data structure and its content.

86% match

world cup score

This visualization displays the first row of the World Cup Score dataset, showing match details such as teams, scores, wickets, and over-by-over run data. It highlights the relationship between the batting team, bowling team, and match outcome, with fields like TotalScoreforTeam1 and TotalWicketforTeam2 visible. The data is parsed from a CSV file using a custom loader and rendered as formatted JSON text via the `main` export, which sets the container’s inner HTML with a `<pre>` element. The code uses standard JavaScript array methods for type conversion and relies on the fetched dataset structure directly.

76% match

World cup score with coordinates

This example displays the first record from a CSV of ICC Cricket World Cup match data (2007–2023), showing over-by-over scoring details with geographic coordinates for the host cities. The visualization parses the CSV using a bundled data import and converts string values to numbers. It renders the JSON representation of the first data row into a preformatted text block, using the container’s innerHTML property. The code relies on the imported dataset and plain JavaScript string interpolation rather than any visualization library, making it a minimal structural preview of the raw data structure.

74% match

playing with json

This visualization displays cricket batting data from a T20 match, showing each batsman’s innings as a horizontal bar spanning from their first to last ball faced. The bar’s height and color encode runs scored before dismissal and strike rate, respectively, using a sequential color scale. Circles mark the final ball of each innings, while text labels annotate standout performances. The chart is rendered as SVG using D3 v5, with data parsed from CSV and scales built via `d3.scaleLinear` and `d3.scaleSequential`, axes via `d3.axisLeft` and `d3.axisBottom`, and color interpolation from `d3.interpolateRdYlGn`.

PPabloEscargot

70% match

Aavinashpandian79@gmail.com

cricket-data-summary

This example presents a summary of cricket player statistics from a CSV dataset, displaying the data in a styled HTML table. It loads the data with `d3.csv`, logs the parsed rows to the browser console, and computes aggregate metrics such as the number of players, average runs, and average strike rate using `d3.mean`. The table’s header and rows are dynamically generated with D3 selections and data joins, while static CSS styles the layout.

Rrahulnathmukkolla@gmail.com

A2 Ques2

This example visualizes the relationship between international cricket players’ runs and wickets, using an area chart to show cumulative trends and colored circles to distinguish individual players. The chart loads CSV data from a GitHub gist, converts numeric string values, and applies D3’s scaleOrdinal with the Category10 scheme for player colors. It renders an SVG area path via d3.area, plots circles per player, and adds a legend using SVG rect and text elements. The code uses d3.csv, d3.scaleLinear, d3.axisBottom, d3.axisLeft, and d3.max from D3 v6.

Final version - Globe

This interactive globe visualization displays cricket match data for cities worldwide, with each city marked by a circle. Users can pan and zoom the SVG-based globe, which uses the D3.js `geoOrthographic` projection. The visualization plots match details, including teams and winning information, into an interactive tooltip when a city is hovered. It leverages `d3.geoPath` for geographic shapes and displays data from a CSV file containing specific match statistics.

Aajaykumarseelam@my.unt.edu

Fork of Activity6_Question_3.1_Scatter Plot

This example visualizes Test Cricket player statistics as a scatter plot, showing the relationship between matches played and total runs scored, with each point colored by the player’s country. The code loads data via `d3.csv` from a GitHub gist, parses numeric fields, and uses `d3.scaleLinear`, `d3.extent`, `d3.axisLeft`, and `d3.axisBottom` to map values and render axes. Circles are drawn with `d3.selectAll` and `enter()`, colored using `d3.scaleOrdinal` with `d3.schemeCategory10`. The SVG output is responsive, sized to the window, and includes labeled axes for matches and runs.