Environmental data quality control
Project description
EnviroDataQC
This library provides a framework for assessing quality of environmental data.
Data is assessed with respect to:
- Data Range
- Data rate of change
- Data flatlining
Additionally, special methods are provided for assessing wind speed and direction data. Data is classified as either suspicious or bad based on either default or custom user settings.
Installation
pip install envirodataqc
Basic Use
Pass data (Pandas dataframe) and measurement type to check_vals(). Dataframe is returned with three new columns: 'flags_range', 'flags_rate', 'flags_flat'. Measurement types supported are defined in 'QCconfig.py'.
Flags:
- 0 : Good
- 1 : Suspicious
- 2 : Bad
Configuration
Change and/or add dictionaries defined in 'QCconfig.py'. Dictionary entries define "good" ranges and "suspicious" ranges for each flag category. Configuration ranges can be non-continuous and any overlap between "good" and "suspicious" ranges will be flagged as "good".
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
Built Distribution
Hashes for envirodataqc-0.1.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 1080c9e3626465670e9fbb30fc5aa305518d4fe20ab26d8fa7f66800196082e7 |
|
MD5 | 5ba996702bb00e8651fc256de3bc220e |
|
BLAKE2b-256 | 995b0b0b85d2ee00ac84881ef5bf97437c68314632a49e0ec944484d59a62cf1 |