rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Pandas for everyone
    sub title: Python data analysis
  title info:
    title: Python data analysis
  name:
    name part: Chen, Daniel Y.
    role:
      role term: creator
    role:
      role term: author.
  type of resource: text
  origin info:
    place:
      place term: mau
    date issued: 2022
    edition: Second edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (512 pages) : illustrations
  abstract: Today, analysts must manage data characterized by extraordinary variety, velocity, and volume. Using the open source Pandas library, you can use Python to rapidly automate and perform virtually any data analysis task, no matter how large or complex. Pandas can help you ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple data sets. Pandas for Everyone, 2nd Edition, brings together practical knowledge and insight for solving real problems with Pandas, even if youre new to Python data analysis. Daniel Y. Chen introduces key concepts through simple but practical examples, incrementally building on them to solve more difficult, real-world data science problems such as using regularization to prevent data overfitting, or when to use unsupervised machine learning methods to find the underlying structure in a data set. Chen gives you a jumpstart on using Pandas with a realistic data set and covers combining data sets, handling missing data, and structuring data sets for easier analysis and visualization. He demonstrates powerful data cleaning techniques, from basic string manipulation to applying functions simultaneously across dataframes. Once your data is ready, Chen guides you through fitting models for prediction, clustering, inference, and exploration. He provides tips on performance and scalability and introduces you to the wider Python data analysis ecosystem.
  note: Daniel Y. Chen.
  note: Includes index.
  subject:
    topic: Python (Computer program language)
  subject:
    topic: Electronic spreadsheets
  subject:
    topic: Electronic data processing
  subject:
    topic: Electronic data processing
  subject:
    topic: Electronic spreadsheets
  subject:
    topic: Python (Computer program language)
  classification: TK5105.52
  classification: 006.3/12
  related item:
    title info:
      title: Addison-Wesley data and analytics series
  identifier: 9780137891153
  identifier: 9780137891146 O'Reilly Media
  identifier: https://proxy.library.tamu.edu/login
  record info:
    record content source: ORMDA
    record creation date: 221130
    record change date: 20260129230155.8
    record identifier: in00004673266
    language of cataloging:
      language term: eng