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reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["elevation","gis","gps","pandas","scipy"],"created_at":"2024-09-24T20:53:11.938Z","updated_at":"2026-03-04T12:31:03.343Z","avatar_url":"https://github.com/aaron-schroeder.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# pandas-xyz\n\nGeospatial calculation accessor for pandas DataFrames.\n\n## Example Usage\n\npandas-xyz provides the `.xyz` DataFrame accessor:\n\n```python\n\u003e\u003e\u003e import pandas as pd\n\u003e\u003e\u003e import pandas_xyz\n\n\u003e\u003e\u003e df = pd.DataFrame.from_dict({\n...   'lat': [40.0, 40.1, 40.3],\n...   'lon': [-105.0, -105.0, -105.0]\n... })\n\n\u003e\u003e\u003e df['displacement'] = df.xyz.ds_from_xy()\n\u003e\u003e\u003e df['displacement']\n0        0.000000\n1    11119.492664\n2    22238.985329\ndtype: float64\n\n\u003e\u003e\u003e df.xyz.s_from_ds()\n0        0.000000\n1    11119.492664\n2    33358.477993\ndtype: float64\n```\n\n## Dependencies and Installation\n\n[Pandas](https://pandas.pydata.org/), [NumPy](https://numpy.org/), and [SciPy](https://www.scipy.org/) are required.\n\nThe package is available on [PyPi](https://pypi.org/project/pandas-xyz) and can be installed with `pip`:\n\n```\n$ pip install pandas-xyz\n```\n\n## License \n\n[![License](http://img.shields.io/:license-mit-blue.svg)](http://badges.mit-license.org)\n\nThis project is licensed under the MIT License. See\n[LICENSE](https://github.com/aaron-schroeder/pandas-xyz/blob/master/LICENSE)\nfile for details.\n\n## Documentation\n\nThe official documentation is hosted at readthedocs: https://pandas-xyz.readthedocs.io/en/stable/\n\n## The Elevation Smoothing Algorithm\n\nThe algorithm I apply to filter elevation time series is based on a paper produced by\nthe National Renewable Energy Laboratory. Their algorithm is meant to smooth the elevation\ntime series of a moving vehicle for more reasonable estimates of road grades for energy consumption\nmodels. This actually isn't that different from my end goal of smoothing elevation series for\nmore reasonable estimates of elevation gain and energy consumption by ambulating humans!\nThe paper is included in the \n[resources folder](https://github.com/aaron-schroeder/pandas-xyz/blob/master/resources/elevation_filtering_nrel.pdf)\n\n## Project Status\n\n### Complete\n\n- Implement an algorithm to smooth noisy elevation time series.\n- Implement a smoothing algorithm for elevation series as a function of\n  distance (similar to how the completed time-smoother works.)\n\n### Current Activities\n\n- Implement an algorithm to smooth GPS position and speed data. \n  Most GPS-enabled activity trackers filter their speed and distance\n  timeseries to remove measurement noise. I want to try and figure out\n  how they do it, then replicate their techniques, and compare the\n  smoothed position data.\n- Develop and document a variety of elevation gain/loss algorithms.  \n- Describe the algorithms in more detail. Maybe in a wiki?\n- Provide references to papers and other resources where I got inspiration\n  for each algorithm.\n\n### Future Work\n\n- Benchmark algorithm performance (speed, accuracy, and consistency):\n   - Generate dummy time series of (distance, elevation) data to check\n     smoothing algorithm.\n   - Generate series of GPS points to obtain elevation coordinates from\n     various DEMs (using [`elevation-query` package](https://github.com/aaron-schroeder/elevation-query))\n     to compare elevation datasets with and without smoothing.\n- Create gain/loss algorithms to emulate those employed by \n  Strava / TrainingPeaks / Garmin.\n\n## Contact\n\nReach out to me at one of the following places!\n\n- Website: [trailzealot.com](https://trailzealot.com)\n- LinkedIn: [linkedin.com/in/aarondschroeder](https://www.linkedin.com/in/aarondschroeder/)\n- Twitter: [@trailzealot](https://twitter.com/trailzealot)\n- Instagram: [@trailzealot](https://instagram.com/trailzealot)\n- GitHub: [github.com/aaron-schroeder](https://github.com/aaron-schroeder)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faaron-schroeder%2Fpandas-xyz","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Faaron-schroeder%2Fpandas-xyz","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faaron-schroeder%2Fpandas-xyz/lists"}