# **spatial.py**
This Library is intended to assist with SPATIAL ANALYSES For purposes of this library, a SPATIAL ANALYSIS is defined as the ANALYSIS of PROPERTIES SURROUNDING a CENTRAL LOCATION via their PROPERTY VALUE and STRAIGHT LINE DISTANCE (SLD) to the CENTRAL LOCATION within a RADIUS OF INTEREST.
## To utilize this library, a CSV FILE is required
* The file MUST be a database CONTAINING PROPERTY ADDRESSES and PROPERTY VALUES
* The file MUST be organized into TWO COLUMNS with the above data
* These columns MUST HAVE NAMES contained in the first cell - this is how we traverse with PANDAS
## To utilize this library GEOPANDAS, GEOPY, and HAVERSINE MUST be INSTALLED
* Either local installation or Google Colab installation via '!pip install #library name#'
## Notes on organization of spatial.py file
* The comments throughout this file explain the purpose of each function via REQUIRES, MODIFIES, and EFFECT (RME) clauses and occasional notes
* This LIBRARY is organized via a CLASS called !!SpatialAnalysis!!. This was the best way I could think to organize all the data with abstraction
* Meaning a class instance MUST be declared to make calls to the functions
* READ the COMMENTS above !!def __init__!! to understand how to declare an instance of the class
# Autors Note
This library was a passion project made for purposes of streamlining work that the Michigan Sports Consulting Group (MSCG) at the University of Michigan does for Economic Analysis Reports. By uploading this, I hope that this work for MSCG will have an impact that outlasts my time in the club. I also hope others find use of this library.
Best,
Jacob Brinkmann
https://www.linkedin.com/in/jacob-brinkmann-567438206/
Raw data
{
"_id": null,
"home_page": "",
"name": "spatdapy",
"maintainer": "",
"docs_url": null,
"requires_python": "",
"maintainer_email": "",
"keywords": "python,spatial,alalysis,MSCG,stadium,Michigan Sports Consulting Group",
"author": "jbrinkm (Jacob Brinkmann)",
"author_email": "<jbrinkm@umich.edu>",
"download_url": "https://files.pythonhosted.org/packages/1e/80/ce9f6fc1c0c66512c5d9f28d0d3f26a2e79d1386d160f344b45014f41e75/spatdapy-0.0.5.tar.gz",
"platform": null,
"description": "\n# **spatial.py**\n\n This Library is intended to assist with SPATIAL ANALYSES For purposes of this library, a SPATIAL ANALYSIS is defined as the ANALYSIS of PROPERTIES SURROUNDING a CENTRAL LOCATION via their PROPERTY VALUE and STRAIGHT LINE DISTANCE (SLD) to the CENTRAL LOCATION within a RADIUS OF INTEREST.\n## To utilize this library, a CSV FILE is required\n* The file MUST be a database CONTAINING PROPERTY ADDRESSES and PROPERTY VALUES\n* The file MUST be organized into TWO COLUMNS with the above data\n * These columns MUST HAVE NAMES contained in the first cell - this is how we traverse with PANDAS\n## To utilize this library GEOPANDAS, GEOPY, and HAVERSINE MUST be INSTALLED\n* Either local installation or Google Colab installation via '!pip install #library name#'\n## Notes on organization of spatial.py file\n* The comments throughout this file explain the purpose of each function via REQUIRES, MODIFIES, and EFFECT (RME) clauses and occasional notes\n* This LIBRARY is organized via a CLASS called !!SpatialAnalysis!!. This was the best way I could think to organize all the data with abstraction\n * Meaning a class instance MUST be declared to make calls to the functions\n * READ the COMMENTS above !!def __init__!! to understand how to declare an instance of the class\n\n # Autors Note\n This library was a passion project made for purposes of streamlining work that the Michigan Sports Consulting Group (MSCG) at the University of Michigan does for Economic Analysis Reports. By uploading this, I hope that this work for MSCG will have an impact that outlasts my time in the club. I also hope others find use of this library. \n\nBest,\nJacob Brinkmann\n https://www.linkedin.com/in/jacob-brinkmann-567438206/\n\n\n",
"bugtrack_url": null,
"license": "",
"summary": "Streamlining Spatial Analyses of Cicular Data Set of Properties",
"version": "0.0.5",
"split_keywords": [
"python",
"spatial",
"alalysis",
"mscg",
"stadium",
"michigan sports consulting group"
],
"urls": [
{
"comment_text": "",
"digests": {
"md5": "fd5cca7761ecb27c719142ec84667c0f",
"sha256": "cda3b49a2c426b7bca84fef80b1d908343752033344fba68f355920b2d5a0af6"
},
"downloads": -1,
"filename": "spatdapy-0.0.5-py3-none-any.whl",
"has_sig": false,
"md5_digest": "fd5cca7761ecb27c719142ec84667c0f",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": null,
"size": 11228,
"upload_time": "2022-12-28T02:52:49",
"upload_time_iso_8601": "2022-12-28T02:52:49.610584Z",
"url": "https://files.pythonhosted.org/packages/b7/5d/668f812f7b31467c9e5cefa8972aefba6c3d32b892b199ba516f518679ef/spatdapy-0.0.5-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"md5": "4d60a2edcc5d713de9802871ba30b82a",
"sha256": "3c063ad3f733b0de4cc48d0165ceb2b7ca38def576d992400f6f08c3b203aee4"
},
"downloads": -1,
"filename": "spatdapy-0.0.5.tar.gz",
"has_sig": false,
"md5_digest": "4d60a2edcc5d713de9802871ba30b82a",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 11960,
"upload_time": "2022-12-28T02:52:55",
"upload_time_iso_8601": "2022-12-28T02:52:55.648163Z",
"url": "https://files.pythonhosted.org/packages/1e/80/ce9f6fc1c0c66512c5d9f28d0d3f26a2e79d1386d160f344b45014f41e75/spatdapy-0.0.5.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2022-12-28 02:52:55",
"github": false,
"gitlab": false,
"bitbucket": false,
"lcname": "spatdapy"
}