http://www.crceanalytics.com/tags/coding/Recent content in Coding on CRC Earth AnalyticsHugoen-usThu, 03 Feb 2022 00:00:00 +0000http://www.crceanalytics.com/posts/automated-qc-of-environmental-data/Thu, 03 Feb 2022 00:00:00 +0000http://www.crceanalytics.com/posts/automated-qc-of-environmental-data/<h2 id="part-2-a-quality-control-api">Part 2: A Quality Control API</h2> <p>This is the second in a two part series on automated quality control of environmental data. The <a href="https://crceanalytics.com/2022/01/13/automated-quality-control-of-environmental-data/">first part</a> gives an overview of quality control with some specific methods for environmental data. In this post, I describe how I created an API (<a href="https://api.crceanalytics.com">api.crceanalytics.com</a>) to automatically flag uploaded data using some of the techniques described in Part 1.</p> <h4 id="motivation">Motivation</h4> <p>A couple years ago I began work on a Python package: EnviroDataQC (<a href="https://github.com/chrisrycx/EnviroDataQC">https://github.com/chrisrycx/EnviroDataQC</a>) that I could use to perform automated quality control on meteorological data being uploaded to <a href="https://dyacon.net">DyaconLive</a>, a web portal for <a href="https://dyacon.com">Dyacon</a> weather stations. The library didn’t need to be overly complex, I just wanted a way to perform range and behavioral checks in a few different contexts without having to re-write quality control code every time. Recently, I thought it might be interesting to build an API that would connect to EnviroDataQC, creating a means for anyone, anywhere to quickly perform data QC. I built a prototype limited to air temperature data at <a href="http://api.crceanalytics.com">api.crceanalytics.com</a> and gave it a simple, interactive front end. I think the concept could be taken a lot further eventually.</p>