Skip to main content

Process and analyze US sewershed data from CWNS

Project description

US Sewersheds

Process and analyze US sewershed data from the Clean Watersheds Needs Survey (CWNS).

Overview

This repository includes code to visualize sewershed interconnections in the US based on the 2022 Clean Watershed Needs Survey. The us_sewersheds folder includes two scripts:

  1. merge_cwns_data.py
    • Merges multiple sources for population served into the primary facilities list.
    • Functions:
      • main(state=None): Main processing function that can process all states or a single state.
      • merge_population_data(facilities_df, ww_df, sso_df): Merges population data from multiple sources.
      • build_sewershed_map(facilities_df): Creates network connections between treatment facilities.
    • Required inputs:
      • data/2022CWNS_NATIONAL_APR2024: Clean Watersheds Needs Survey 2022 dataset
        • FACILITIES.csv: Main facilities data
        • FACILITY_PERMIT.csv: Facility permit information
        • AREAS_COUNTY.csv: County area information
        • FACILITY_TYPES.csv: Facility type information
        • FLOW.csv: Flow data
        • POPULATION_WASTEWATER.csv: Wastewater population data
        • POPULATION_WASTEWATER_CONFIRMED.csv: Confirmed wastewater population data
        • POPULATION_DECENTRALIZED.csv: Decentralized population data
        • DISCHARGES.csv: Discharge information
  2. sewersheds_app.py
    • Deploys Streamlit application to visualize different sewersheds in the US, by state and county

Installation

From PyPI

pip install us-sewersheds

From Source

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

us_sewersheds-0.1.2.tar.gz (14.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

us_sewersheds-0.1.2-py3-none-any.whl (14.5 kB view details)

Uploaded Python 3

File details

Details for the file us_sewersheds-0.1.2.tar.gz.

File metadata

  • Download URL: us_sewersheds-0.1.2.tar.gz
  • Upload date:
  • Size: 14.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for us_sewersheds-0.1.2.tar.gz
Algorithm Hash digest
SHA256 a2700829acfef1a0c134bce9d54c75ce276729192356a4a9c9bd37e111430f85
MD5 5d6aebf78d3a715592bfb60febb0a0a5
BLAKE2b-256 d504baee8b06397fb3ad0fd19b147e855a4f2fb5fa396487ee12a9fd4abc4ab2

See more details on using hashes here.

Provenance

The following attestation bundles were made for us_sewersheds-0.1.2.tar.gz:

Publisher: publish.yml on dalyw/us-sewersheds

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file us_sewersheds-0.1.2-py3-none-any.whl.

File metadata

  • Download URL: us_sewersheds-0.1.2-py3-none-any.whl
  • Upload date:
  • Size: 14.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for us_sewersheds-0.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 c290215e1a8025e86f5bb3162b5162a072e3fb5858cb94324cb334b514db44ae
MD5 173c7551237a21d5847173ac604466bf
BLAKE2b-256 8a89e0a5ea58460707313ffa6776738905042c4675e94e84f01116459a5d39fa

See more details on using hashes here.

Provenance

The following attestation bundles were made for us_sewersheds-0.1.2-py3-none-any.whl:

Publisher: publish.yml on dalyw/us-sewersheds

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

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