envirodataqc 0.2.0

Environmental data quality control

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".