Metadata-Version: 2.1
Name: envirodataqc
Version: 0.1.1
Summary: Environmental data quality control
Home-page: https://github.com/chrisrycx/EnviroDataQC
Author: Chris Cox
Author-email: chrisrycx@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: pandas

# 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".



