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数据采集与分析

University of Edinburgh:INF2-FDS — Foundations of Data Science

Section titled “University of Edinburgh:INF2-FDS — Foundations of Data Science”
  1. [1]
    D. Sterratt and K. Gal, “Foundations of Data Science (Inf2-FDS) Lecture Notes.” The University of Edinburgh, Jan. 19, 2026. Accessed: Oct. 31, 2026. [PDF]. Available: https://opencourse.inf.ed.ac.uk/archives/25-26/sites/default/files/2026-01/FDS-lecture-notes-2026-01-19.pdf
  2. [2]
    “Informatics 2 – Foundations of Data Science: Labs.” The University of Edinburgh. Accessed: Oct. 31, 2026. [Jupyter notebooks and PDF]. Available: https://opencourse.inf.ed.ac.uk/archives/25-26/node/549.html
  3. [3]
    “Informatics 2 – Foundations of Data Science: Workshops.” The University of Edinburgh. Accessed: Oct. 31, 2026. [HTML and PDF]. Available: https://opencourse.inf.ed.ac.uk/archives/25-26/node/554.html

这里列出常用数据集的主要目的并不是建议大家使用这些数据集完成课外项目。相反,从 GitHub 可以很容易搜索到大量使用这些数据集的仓库,因此我希望大家尽量避免直接使用它们,而是自己去不同的领域发现需求、收集并清洗数据。

  1. [4]
    A. Go, R. Bhayani, and L. Huang, “Sentiment140.” Accessed: Nov. 02, 2026. [CSV]. Available: https://www.kaggle.com/datasets/kazanova/sentiment140
  2. [5]
    CrowdFlower, “Twitter US Airline Sentiment.” Figure Eight, Oct. 16, 2019. Accessed: Nov. 03, 2026. [CSV and SQLite]. Available: https://www.kaggle.com/datasets/crowdflower/twitter-airline-sentiment
  3. [6]
    GroupLens Research, “MovieLens.” GroupLens Research. Accessed: Nov. 03, 2026. [CSV and text]. Available: https://grouplens.org/datasets/movielens/
    机构:
    • University of Minnesota
    免费资源:
    MovieLens 32M
    MovieLens 20M
    MovieLens 100K
  4. [7]
    “MIND: MIcrosoft News Dataset.” Microsoft Research. Accessed: Nov. 03, 2026. [TSV]. Available: https://msnews.github.io/
    免费资源:
  5. [8]
    J. McAuley and J. Leskovec, “Social circles: Facebook.” in Stanford Large Network Dataset Collection. Accessed: Nov. 02, 2026. [Text edge lists and node features]. Available: https://snap.stanford.edu/data/ego-Facebook.html
  6. [9]
    “Reddit.” in GraphSAGE. Accessed: Nov. 03, 2026. [JSON, NumPy and text]. Available: https://snap.stanford.edu/graphsage/#datasets
  7. [10]
    “Protein-Protein Interactions.” in GraphSAGE. Accessed: Nov. 03, 2026. [JSON, NumPy and text]. Available: https://snap.stanford.edu/graphsage/#datasets
  8. [11]
    W. W. Zachary, “Zachary’s Karate Club.” Accessed: Nov. 02, 2026. [Graph and GML]. Available: https://networkx.org/documentation/stable/reference/generated/networkx.generators.social.karate_club_graph.html
  9. [12]
    Y. LeCun, C. Cortes, and C. J. C. Burges, “The MNIST database of handwritten digits.” Accessed: Nov. 03, 2026. [IDX]. Available: https://www.tensorflow.org/datasets/catalog/mnist
  10. [13]
    “diamonds.” in ggplot2. Accessed: Nov. 02, 2026. [R data and CSV]. Available: https://ggplot2.tidyverse.org/reference/diamonds.html
  11. [14]
    “TLC Trip Record Data.” New York City Taxi and Limousine Commission. Accessed: Nov. 02, 2026. [Parquet and CSV]. Available: https://www.nyc.gov/site/tlc/about/tlc-trip-record-data.page

数据库分析性能基准与数据生成工具

Section titled “数据库分析性能基准与数据生成工具”
  1. [15]
    Transaction Processing Performance Council, TPC Benchmark H (Decision Support): Standard Specification, TPC-H, San Francisco., Apr. 28, 2022. Accessed: Nov. 02, 2026. [Online]. Available: https://www.tpc.org/tpch/
  2. [16]
    Transaction Processing Performance Council, TPC Benchmark DS: Standard Specification, TPC-DS, Nov. 21, 2024. Accessed: Nov. 02, 2026. [Online]. Available: https://www.tpc.org/tpcds/
  1. [17]
    “Sample datasets,” Microsoft Learn. Accessed: Nov. 03, 2026. [Online]. Available: https://learn.microsoft.com/en-us/azure/databricks/discover/databricks-datasets
  2. [18]
    “Azure Open Datasets,” Microsoft Learn. Accessed: Nov. 03, 2026. [Online]. Available: https://learn.microsoft.com/en-us/azure/open-datasets/dataset-catalog