Atmotube Data Parser

Python-based pipeline to parse Atmotube data (from PRO or PRO 2) using keyword-based detection into subdivided data frames (or save as a merged CSV), ready for spatial and/or time series analysis.

Features:

• Keyword-based column detection (robust to messy exports)
• Timezone and local time inference from GPS coordinates
• Breakdown of each sensor and variable used by Atmotube PRO/PRO2, includes notes and reference sources

How to use

1. Upload raw CSV file to 1.upload
2. Install dependencies:

pip install pandas tzfpy

or

conda install -c conda-forge pandas tzfpy

4. Follow intructions in the 2.make

# Open a terminal in VS Code (Ctrl+Shift+`)
# Set working directory to current directory `cd .`
# Test run this script as `python 2.make/atmoData.py example_ext.csv`
# Run it with your actual csv.

6. Automatically saves the parsed CSV to 3.save

Example data taken from https://support.atmotube.com/en/articles/13002682-history-mode-overview