This project is about visualizing personal GPS data with Python. The goal was to explore the different ways of visualizing the GPS data which I have collected during my stay in New York.
- numpy fundamental package for scientific computing with Python
- matplotlib python 2D plotting library
- gdal python bindings for Geospatial Data Abstraction Library (and OGR)
- Basemap plot on map projections using matplotlib
This project was implemented on Windows x64 and with Python 2.7 and the GDAL binaries are installed through the help of the following link: Installing GDAL for Windows.
All the source files in the src folder produce images which are saved in the visualization folder.
- simple_scatter.py Scatter plot visualization of the data set on top of the neighborhoods.
- point_heatmap.py Previous visualization with added heatmap layer.
- compute_neighborhood_histogram.py This source file is necessary to compute the number of points for each neighborhood and visualize a bar chart histogram.
- neighborhood_heatmap.py Heatmap visualization with histogram bins for each neighborhood. neighborhood_histogram.npy is necessary to run this visualization, which is computed by compute_neighborhood_histogram.py.
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The example data set used for the visualizations is from the Citibike System Data, which can be found on the real-time Citibike station feed.
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The NYC Neighborhood boundaries are used from the GeoJSON at the Pediacities NYC Neighborhoods.
