Skip to main content
SimilarExport ZIP
100%

Television Show Ratings

✓ Published0🌍 Public
Vvwm
Last edited Sep 17, 2019
Created on Sep 4, 2019

This example displays basic metadata about a television show ratings dataset, showing the file size, row count, and column count in a large text format. The page loads CSV data from a Tidy Tuesday repository using `d3.csv` and reports the results. The visualization is intentionally minimal, using a `<pre>` element to render the computed statistics rather than drawing charts or graphs. The code also includes commented-out alternatives using `fetch` with `async`/`await` and `d3.csvParse`, demonstrating different approaches to loading and parsing the same data source.

AI-generated description

This Television Show Rating dataset originates from R for Data Science's Tidy Tuesday weekly event for January 8, 2019. It describes television show ratings by season, genre, and release date.

Questions for consideration:

  • Do certain genres garner better ratings when combined with other genres? (Are there "good" or "bad" genre pairings that become evident?)
  • Is there a correlation between the release date and rating?
  • How do ratings tend to change across seasons? (Does this rating change differ across genres?)

Genre is categorical. Rating and share are quantitative.

MIT Licensed

Similar vizzes

Loading thumbnail…

TV_Shows_data

This example displays a plain-text summary of the TV_Shows_data CSV file, reporting its size in kilobytes, row count, and column count. It loads the dataset from a GitHub-hosted CSV using the `d3.csv` method, then formats the output with `d3.csvFormat`. The visualization is minimal, showing no charts, but it demonstrates the initial data-loading and metadata-reporting step using D3 v5.

LlzlazmSylas
80% match
Loading thumbnail…

Television Show Ratings - Rating by Show

This visualization displays average television show ratings, filtered to exclude values below 9.1 and sorted by rating, with point size encoding rating share. Data comes from a CSV file, processed via `d3.csv`, and the chart is built using the Vega-Lite API with `vl.markPoint`, encoding fields for title, rating, and share. The visualization is rendered as a static SVG using the Vega rendering engine, with custom styling applied through a config object.

Vvwm
75% match
Loading thumbnail…

Fetch CSV DATA

This example demonstrates loading a remote CSV file with D3 and displaying basic dataset metrics—file size in kilobytes, row count, and column count—in large, styled text. The visualization relies on `d3.csv` from d3-fetch to parse the data, then uses `d3.csvFormat` to measure the formatted output length and accesses `data.length` and `data.columns` for row and column tallies. The result updates a `<pre>` element via React’s production build, though the core data fetching and parsing use D3 v4 and v7 APIs alongside native `fetch` in commented alternatives.

Mmartfhill
73% match
Loading thumbnail…

Fetching data

This example displays basic metadata about a fetched CSV file, showing its size in kilobytes, row count, and column count in large text. It loads a named CSS colors dataset from a GitHub gist using the `d3.csv` method with a Promise-based `.then()` callback, then counts rows via `txt.length` and columns through `txt.columns.length`. The text size is computed from `d3.csvFormat(txt).length`. The page uses D3 v7 and renders the resulting information inside a `<pre>` element.

SShanoy
73% match
Loading thumbnail…

Untitled

This example displays a concise summary of a CSV dataset loaded from a remote URL, showing the file size in kilobytes, the number of rows, and the number of columns. Using D3.js v5, it calls `d3.csv` to fetch and parse the data, then uses `d3.csvFormat` and `data.columns` to compute the statistics, displaying them in a large HTML `<pre>` element. The visualization demonstrates asynchronous data loading with promises, highlighting the simplicity of the `d3.csv` API over raw `fetch` and `await` alternatives.

Cchar0496
72% match
Loading thumbnail…

Data Visualization 1

This example displays basic metadata about a CSS-named-colors dataset loaded from a CSV file: the approximate file size in kilobytes, the number of rows, and the column names. It uses D3 v5’s `d3.csv` to fetch and parse the data, then writes the computed statistics into a large `<pre>` element on the page. The code also includes commented-out alternatives using `fetch` and `d3.csvParse` with async/await syntax.

JJohn Jeevasaeyan
72% match
Loading thumbnail…

Data Table Summary

This example displays a plain-text summary of a satellite dataset, showing the row count, column count, and file size in kilobytes, followed by the first ten rows formatted as JSON. The visualization uses D3 v5’s `csv` and `csvFormat` functions to parse and measure the data, then appends the results to the body as `pre` elements. The dataset covers man-made satellites as of April 2018, sourced from the Union of Concerned Scientists.

RRyan Fleming
72% match
Loading thumbnail…

Data Table Summary

This example displays a plain-text summary of a loaded CSV file, showing the total row count, column count, and file size in kilobytes, followed by the first ten rows formatted as JSON. It imports `select`, `csv`, and `csvFormat` from D3 v5 to fetch `data.csv` and compute the byte length. The output renders in a monospace `<pre>` element styled with green-on-black terminal colors. The dataset describes daily high and low stock prices for several tickers, sourced from a 2018 United Nations population report.

Vveagy
72% match