Movies_Dataset

Movie Stats Scatter Plot Iteration 5

This interactive scatter plot visualizes movie statistics from a CSV dataset, allowing users to compare variables such as IMDB rating, revenue, runtime, and year. Users can filter points by genre through colored checkboxes, search for specific actors, and switch the x- and y-axis among six quantitative fields. Clicking a circle displays the movie’s title. The visualization uses D3 v7 APIs like `scaleLinear`, `axisLeft`, and `axisBottom` to render axes and circles, with SVG elements updated dynamically via `selectAll` and `join`.

82% match

Movie Stats Scatter Plot

This visualization plots movie ratings against box office revenue using a D3 v7 scatter plot, with data from a CSV file of film statistics. The plot displays each movie as a circle, and the interface includes checkboxes for filtering by genre, which dynamically update the visible data points using a bitstring representation. The code uses `d3.csvParse`, `d3.scaleLinear`, and `d3.extent` to handle data parsing and scaling, while the interactive filtering logic is implemented in the `dotAppears` function within `scatterPlot.js`.

81% match

Movies Scatter Plot

A scatter plot displays movie ratings against release dates from 1958 to 2019, with each red semi-transparent circle representing a single film’s score. The visualization uses D3 v5’s `scaleLinear`, `axisBottom`, and `axisLeft` to map the data, while `csv()` loads the dataset and SVG renders the circles. Grid lines extend from both axes, and custom axis labels and a title annotate the chart.

DD0no

80% match

Movie Stats Scatter Plot Iteration 4

This interactive scatter plot displays movie statistics from the data.csv file, allowing users to toggle genre filters via checkboxes and select which attributes (e.g., IMDB rating, Revenue, Runtime) map to the x- and y-axes through radio buttons. D3 v7 powers the scales, axes, and circle rendering, with genres color-coded and hover events showing the movie title. The implementation uses d3.scaleLinear, d3.axisBottom/axisLeft, and d3.csvParse to load data and update the visualization through a state-driven design.

80% match

Movie Stats Scatter Plot Iteration 7

This interactive visualization lets users explore IMDB data for roughly 1,000 movies through a customizable scatter plot. Users select which genres or a specific actor to display, and choose which metrics (year, runtime, rating, metascore, votes, or revenue) appear on each axis. Hovering over a dot reveals the movie title. Built with D3 v7, it uses `d3.scaleLinear` and `d3.axisLeft`/`axisBottom` to render an SVG chart, with data loaded from a CSV file.

cars scatter plot

This scatter plot visualizes the relationship between movie ratings and ranks across a dataset of films, with each circle representing a movie. The visualization uses D3 v5 within a React framework, leveraging `d3.csv` for data loading, `d3.scaleLinear` for axis scaling, and `d3.axisBottom` and `d3.axisLeft` for tick marks and gridlines. Rendered as an SVG, the plot includes axis labels, a title, and red semi-transparent circles. The data comes from an external `movies.csv` file, and the code parses numeric fields before plotting.

AAkhilesh7866

cars scatter plot

AAkhilesh7866

Fork of Loading and Parsing CSV Data with D3.js

This visualization displays metadata about a movie ranking dataset loaded from a CSV file, showing the file size, row count, and column count. The webpage presents this information as text beneath a static SVG title image. The example uses D3.js version 7 and the `d3.csv` method to asynchronously fetch and parse the remote CSV data from a GitHub gist, while also using `d3.csvFormat` to calculate the file size in kilobytes. The page layout is styled with custom CSS and renders the results in a preformatted text element.

SSharmilaChowdhari