Skip to main content

This library code execute aggregate analysis for the Quality of Life Exporer variables

Project description

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()

A.withinNPA('NPA','Banks','BanksNPA') A.withNPAID('CreditUnion','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 no arguments.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
      • Point feature class to be aggregated
      • Name of output feature class
    • The withNPAID method: This method assign NPA IDs to point feature classes that are completely within each NPA

      • Point feature classes
      • NPA feature class
      • Name of output feature class

License This project is licensed under the MIT License - see the LICENSE file for details.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

qolagg-1.0.tar.gz (3.9 kB view details)

Uploaded Source

Built Distribution

qolagg-1.0-py3-none-any.whl (4.6 kB view details)

Uploaded Python 3

File details

Details for the file qolagg-1.0.tar.gz.

File metadata

  • Download URL: qolagg-1.0.tar.gz
  • Upload date:
  • Size: 3.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.7.9

File hashes

Hashes for qolagg-1.0.tar.gz
Algorithm Hash digest
SHA256 bb80052eb3b88279ef89be56b52580e286afd4326e33c73a51d81ef0fb9cf4af
MD5 a616888a1708341cce2cfa0b3ebfea63
BLAKE2b-256 59216e4a67e636b5e45a60ad879584dc1f1597b52aa55d451911a397c04681e5

See more details on using hashes here.

File details

Details for the file qolagg-1.0-py3-none-any.whl.

File metadata

  • Download URL: qolagg-1.0-py3-none-any.whl
  • Upload date:
  • Size: 4.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.7.9

File hashes

Hashes for qolagg-1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 c281061ddbda0914a64559b7144369bf83d3b39edeaf42338ee8bf9b7ec2a126
MD5 51609cd5a6c57118d833e6b06430e409
BLAKE2b-256 4b6b7c5efcf17317eedbc9d72574a304e7119120919dfe9a29059c059e457cd1

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page