2018 International Football TransferMarket Visualization in Bokeh

The goal of this project is to scrape and crawl through multiple pages of TransferMarket.com and create an interesting Bokeh Visualization. The data was scrapped using BeautifulSoup and compiled into a SQLite database. Then SQL queries were constructed and the query results were loaded into a Pandas to allow for easier data manipulation. Finally, that data was loaded into Bokeh to create a Scatter Plot that explores the relationships between a soccer teams A) Average Squad Age B) 2018 Squad Market Value and C) Number of Foreign Players found in each Squad.

Derrida: Visualization of Derrida’s Margin in D3

Jacques Derrida is one of the major figures of twentieth-century thought, and his library – which bears the traces of decades of close reading – represents a major intellectual archive. The Princeton University Library (PUL) houses Derrida’s Margins, a website and online research tool for the annotations of Jacques Derrida. We used data collected from this project to create visualizations of the references used throughout Derrida’s De la grammatologie.

In this interactive visualization for Derrida’s De la grammatologie we represent each book referenced (nodes) and the locations where each book is referenced in the work (lines connecting nodes to the x-axis). The x-axis represents De la grammatologie from start to finish, and the y-axis represents the years in which each referenced book was published. The color of each node indicates the language in which each referenced book was published, and the position of each node is an averaged position among the pages at which the node was references in De la grammatologie. A brush tool is implemented along the x-axis to select ranges of De la grammatologie and references made within the selected range. By mousing over each node, the book title, author, and publication year are displayed.

This code can be adapted to create an interactive visualization for any data set, either for book references or another type, which includes many entries, an x-axis location for each entry, a y-axis location for each entry, and information to display with the mouse-over feature. The interactive and visual components are most interesting when entries are not discrete, and can be connected with a significant frequency to many locations along the x-axis.


Mapping with D3: Library of Congress books over time

In May 2017, the US Library of Congress made the largest release of digital records in its history – metadata for over 25 million books, maps and recordings. People immediately started making some pretty cool visualizations to explore patterns in the data, or demonstrate the incredible size of the release. This page follows my process of building an animated D3 map visualization, from data cleaning to adding features. Each of the pages below covers one step in the process. Jump to the last page to explore the visualization.

  1. Preparing the Data – Parse massive xml record files, cache and geocode subject locations, aggregate for our visualization.
  2. Basic Animation – Build a D3 map that animates changing numbers of records about each country over time.
  3. Add a Tooltip – Add a tooltip to display country name on hovering. Select a country on click to show record counts for that country.


Still frame of the animated map created in this project.