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Loading and Parsing IMDb Top 250 CSV Data

✓ Published0🌍 Public
YYichen Li
Last edited Sep 29, 2021
Created on Sep 8, 2021

This example demonstrates loading and parsing the IMDb Top 250 dataset, displaying the file size in kilobytes, row count, and column count in large text. The visualization uses d3.csv to fetch and parse a remote CSV file from a GitHub gist, then applies d3.csvFormat and data.length to compute summary metrics. The code also includes commented alternatives using fetch, async/await, and d3.csvParse, as well as a nested Promise-based “pyramid of doom” approach. No graphical chart is rendered; the output is purely textual summary statistics.

AI-generated description

Description:

This program loads and parses the IMDb Top 250 Dataset

Ideas for Questions and Tasks

  1. What are the movies that have the highest scores or most votes in each year?
  2. What is the distribution of genre in each year?
  3. What movies have been on the list for most times?

Special Types of Attributes

  • Genre is categorical
  • RunTime and IMDByear are ordinal
  • Ranking is ordinal
  • Rating and Votes are quantitive
MIT Licensed

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