# Aggregate Data Analysis with ArcPy
This package provides a Python class `aggregate` tailored for analyzing and aggregating spatial data using ArcPy. The class is designed for Urban Institute's Quality of Life (QOL) variables, offering methods for merging, spatial joining, and exporting data to CSV files.
## Installation
Install `aggregate` from PyPI using pip:
pip install aggqol
# Usage
import aggqol as ag
A = ag.aggregate('Banks')
A.withinNPA('NPA','BanksNPA')
A = ag.aggregate('CreditUnion')
A.withNPAID('NPA', 'CreditNPAID')
## Methods
Methods
`__init__(self, InFeatureClass)`
Initialize the aggregate class with the input feature class.
`merge(self, *FeatureClassesToBeMerged)`
Combine feature classes from multiple sources into one feature class for analysis.
`withinNPA(self, NPA, OutputName)`
Aggregate all points feature classes that are completely contained by an NPA polygon.
`withNPAID(self, NPA, OutputName)`
Assign NPA ID to all point feature classes that are completely within an NPA.
`exportcsv(self, OutputDirectory, PopulationFile, PopulationColumn, FileName)`
Export the results to a CSV file, joining population data and calculating summary statistics.
## Additonal Information
- The aggregate class is initialized with one argument ( Point feature classes ).This class has two methods:
- The *withinNPA* method: This method aggregates point features classes that are completely contained by each NPA
The withinNPA method takes two arguments:
- NPA feature class
- Name of output feature class
- The *withNPAID* method: This method assign NPA IDs to point feature classes that are completely within each NPA
- NPA feature class
- Name of output feature class
License
This project is licensed under the MIT License - see the LICENSE file for details.
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"description": "\n# Aggregate Data Analysis with ArcPy\n\nThis package provides a Python class `aggregate` tailored for analyzing and aggregating spatial data using ArcPy. The class is designed for Urban Institute's Quality of Life (QOL) variables, offering methods for merging, spatial joining, and exporting data to CSV files.\n\n## Installation\n\nInstall `aggregate` from PyPI using pip:\n\n\npip install aggqol\n\n# Usage\n\nimport aggqol as ag\n\nA = ag.aggregate('Banks')\n\nA.withinNPA('NPA','BanksNPA')\n\nA = ag.aggregate('CreditUnion')\n\nA.withNPAID('NPA', 'CreditNPAID')\n\n## Methods\n\nMethods\n`__init__(self, InFeatureClass)`\n\nInitialize the aggregate class with the input feature class.\n\n`merge(self, *FeatureClassesToBeMerged)`\n\nCombine feature classes from multiple sources into one feature class for analysis.\n\n`withinNPA(self, NPA, OutputName)`\n\nAggregate all points feature classes that are completely contained by an NPA polygon.\n\n`withNPAID(self, NPA, OutputName)`\nAssign NPA ID to all point feature classes that are completely within an NPA.\n\n`exportcsv(self, OutputDirectory, PopulationFile, PopulationColumn, FileName)`\n\nExport the results to a CSV file, joining population data and calculating summary statistics.\n\n## Additonal Information\n\n- The aggregate class is initialized with one argument ( Point feature classes ).This class has two methods:\n - The *withinNPA* method: This method aggregates point features classes that are completely contained by each NPA \n The withinNPA method takes two arguments: \n - NPA feature class\n - Name of output feature class\n \n - The *withNPAID* method: This method assign NPA IDs to point feature classes that are completely within each NPA\n - NPA feature class \n - Name of output feature class\n\nLicense\nThis project is licensed under the MIT License - see the LICENSE file for details.\n",
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