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: Learn to create a visualization of aggregated time data in Python with data from ACEA (2020)
  name:
    name part: Hildén, Jonatan
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Koivunen-Niemi, Laura
    role:
      role term: author.
  type of resource: text
  origin info:
    place:
      place term: enk
    date issued: 2022
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource : illustrations
  abstract: This dataset outlines how to create a line chart of aggregated time series data points using new vehicle registration data from the European Automobile Manufacturers' Association. Aggregating data points by time is generally used to minimize temporal variation in the dataset and, thus, better bring out large-scale trends in the series. Methods for aggregation are many, but foremost among them are summing and averaging entries into a different unit of time. You will learn to identify ideal use cases and best practices for employing time aggregation for data visualization in your work. The dataset file is accompanied by a Student Guide and a How-to Guide for creating this chart type using Python.
  target audience: specialized
  note: Jonatan Hildén, Laura Koivunen-Niemi.
  subject:
    topic: Information visualization
  subject:
    topic: Python (Computer program language)
  subject:
    topic: Visualisation de l'information
  subject:
    topic: Python (Langage de programmation)
  subject:
    topic: Information visualization
  subject:
    topic: Python (Computer program language)
  classification: QA76.9.I52 H55 2022
  classification: 001.4226
  identifier: 9781529605211
  identifier: 1529605210
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: SGPBL
    record creation date: 220322
    record change date: 20240923170202.7
    record identifier: in00005493205
    language of cataloging:
      language term: eng