MartiHearst

@MartiHearst·7 public vizzes

iSchool GeoVisualization Workshop

This interactive map visualizes New York City motor vehicle crash locations using Mapbox GL and D3.js. The page displays raw crash data points from a GeoJSON file alongside hexbin aggregations loaded from a separate processed JSON source. A dark map style provides the base layer, with the map centered on the city at zoom level 10. The implementation initializes a Mapbox GL map instance and references two remote data URLs, showing how to combine geographic data sources in a workshop template.

Apr 11, 2018

Loading thumbnail…

iSchool GeoVisualization Workshop

This example presents a dark-themed interactive map of New York City motor vehicle crash locations, visualized as a point dataset over a base map. The view centers on the city and uses an initial zoom level of 10, with a full-screen map container. The visualization relies on the Mapbox GL JS API (v0.43.0) to render the base map and manage user interaction. It loads crash data from a remote GeoJSON file and also references a second JSON file containing hexbin aggregates, although the code shown only initializes the map and sets the access token. The map is configured with the "dark-v9" style, and D3 v4 is included in the page.

Apr 11, 2018

Loading thumbnail…

iSchool GeoVisualization Workshop

This example shows a map of New York City traffic crashes, with each crash represented by a colored circle that indicates the type of severity (injury, fatality, or no injury). The map is built using Mapbox GL JS for the interactive basemap, while D3.js (v3) handles fetching the GeoJSON crash data and styling the circle layer’s color and radius. The circle size scales dynamically with zoom level, and Turf.js is loaded but not used in the visible code. The data comes from the `nyc_crashes.geojson` file hosted on GitHub.

Apr 10, 2017

Loading thumbnail…

Gist 4be75194a32c761f2a20

This example demonstrates how to use NLTK's frequency distribution object to analyze word frequencies in the Monty Python and the Holy Grail text (text6). The code imports the NLTK book module, creates a FreqDist from the text, and displays the top 50 word-frequency pairs, revealing unexpected results. The notebook then poses tasks for modifying the text and generating cumulative frequency plots, while also showing list comprehensions to filter words by length and frequency. The analysis relies on NLTK's FreqDist and the pre-loaded text corpus from the nltk.book module.

Sep 6, 2014

Loading thumbnail…

Gist 18319c4f30bf20182aad

This example uses an iPython Notebook to teach basic Python and Markdown skills. It shows a sequence of tasks for editing text cells, writing code, and manipulating strings, using the NLTK library to process a sentence. The notebook’s cells contain instructional headings, markdown explanations, and Python code inputs with output. The visualization is the notebook itself, rendered as a static document with WebGL, demonstrating its interactive, code-driven structure.

Sep 5, 2014

Loading thumbnail…

Gist 2116a7bda7ef9a6364f3

This example demonstrates how to use NLTK’s frequency distribution object to analyze word frequencies in the pre‑loaded text of Monty Python and the Holy Grail. It first displays the top 50 most frequent words, then guides the viewer through tasks that involve examining the raw text, modifying it, and rerunning the frequency calculation. A cumulative frequency plot is generated, and a list comprehension isolates words longer than five characters that occur at least five times, sorted alphabetically. The code relies on NLTK’s `FreqDist` and the `nltk.book` collection.

Sep 5, 2014

Loading thumbnail…

Gist 9176cfc4d4149c55845f

This IPython Notebook tutorial shows users how to get comfortable with markdown cells and basic Python coding tasks. It walks through editing text with markdown syntax and writing small code snippets, such as splitting a sentence into a list of words and using list splicing to extract the last few items. The notebook relies on the IPython Notebook API for rendering and executing cells, with all code examples written in standard Python.

Sep 4, 2014