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Data Analysis & Visualization

The library offers support identifying and using the best software to analyze or visualize your data.

Analyzing Data

The Claremont Colleges Library offers some support for data analysis, but our resources are generally not as extensive as those of the colleges. We cannot, for example, provide in-depth software training for many of the tools used for data analysis. However, we can refer you to appropriate resources at the colleges and to resources in our collections, or online, for learning more about how to use these tools.

  • Quantitative data analysis can be done with a number of software tools:
    • R is free and open source.
    • SPSS and Stata are proprietary applications
      • Jeanine Finn, the Data Services Librarian, can provide basic/introductory support for SPSS analysis software.
  • Qualitative data analysis can also be supported by software. This approach is often referred to as computer assisted qualitative data analysis (CAQDAS).
    • NVivo and ATLAS.ti are popular proprietary tools.
  • To find out which proprietary tools for data analysis are available to you, contact your college’s Information Technology department.
Visualizing Data

Data visualization refers to many different forms of using visual and design elements to help communicate ideas from large sets of data.

Tools available:

  • Spreadsheet tools (such as Excel or Google Sheets) can offer some basic data visualization support such as charts and graphs for describing your data.
  • Tableau is a popular tool for many types of data visualization. It is available on computers in the Digital Tool Shed and the Digital Research Studio.
  • Free data visualization tools:
    • RAWgraphs describes itself as an “open source data visualization framework” for making complex spreadsheet data visually understandable.
    • Palladio is an open source project from Stanford designed to support unique visualizations of historical and humanistic datasets.
  • Infographics: There are quite a few free tools available for creating infographics:
Get Help with Data Analysis & Visualization
Jeanine Finn
Data Science & Digital Scholarship Coordinator