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16: Visualizing data

  • Page ID
    3279
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    So far we have been learning the Python language and then learning how to use Python, the network, and databases to manipulate data. In this chapter, we take a look at three complete applications that bring all of these things together to manage and visualize data. You might use these applications as sample code to help get you started in solving a real-world problem. Each of the applications is a ZIP file that you can download and extract onto your computer and execute.

    • 16.1: Building a Google map from geocoded data
      In this project, we are using the Google geocoding API to clean up some user-entered geographic locations of university names and then placing the data on a Google map.
    • 16.2: Visualizing Networks and Interconnections
      In this application, we will perform some of the functions of a search engine. We will first spider a small subset of the web and run a simplified version of the Google page rank algorithm to determine which pages are most highly connected, and then visualize the page rank and connectivity of our small corner of the web. We will use the D3 JavaScript visualization library http://d3js.org/ to produce the visualization output.
    • 16.3: Visualizing mail data
      In this application, we will perform some of the functions of a search engine. We will first spider a small subset of the web and run a simplified version of the Google page rank algorithm to determine which pages are most highly connected, and then visualize the page rank and connectivity of our small corner of the web. We will use the D3 JavaScript visualization library http://d3js.org/ to produce the visualization output.


    This page titled 16: Visualizing data is shared under a CC BY-NC-SA 4.0 license and was authored, remixed, and/or curated by Chuck Severance via source content that was edited to the style and standards of the LibreTexts platform.

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