This repository contains data collected from a single Open Agriculture Personal Food Computer, that has been running at the Cooper Hewitt Museum since May, 2019.
A time lapse MP4 created from images collected between 2019-05-06 11:07:01 UTC and 2019-09-08 09:03:12 UTC.
The images were downloaded using wget
from the URLs in the data/Camera-Top_URL.csv
file, and then ffmpeg
was used to create the timelapse mp4.
You'll find a raw download of the data from our Google BigQuery backend in the raw_data
directory.
In the data
directory you'll find the data split out into individual CSV files. The python script that was used to do that is the split_raw_data.py
file.
(Note there was a spelling error in our data processing code, hence celcius
)
Here are some stats on the split out data:
filename | datapoints | Max Val | Min Val | Mean Val | Standard Dev |
---|---|---|---|---|---|
air_carbon_dioxide_ppm_T6713-Top.csv | 73069 | 2279 | 0 | 624.95 | 168.51 |
air_humidity_percent_SHT25-Top.csv | 73072 | 65 | 41 | 53.14 | 4.38 |
air_temperature_celcius_SHT25-Top.csv | 73074 | 27.0 | 17.0 | 20.91 | 1.39 |
water_electrical_conductivity_ms_cm_AtlasEC-Reservoir.csv | 73078 | 26.1 | 0.0 | 10.46 | 6.01 |
water_potential_hydrogen_AtlasPH-Reservoir.csv | 73080 | 8.18 | 5.25 | 6.33 | 0.68 |
water_temperature_celcius_AtlasTemp-Reservoir.csv | 73084 | 779.43 | 14.64 | 19.7 | 14.57 |
There are obvious errors in the data, such as the water temperature reaching 779 degrees C, well above the boiling point.
In the notebooks
directory you'll find a Jupyter notebook that was used to produce some graphs of the data. You can see the HTML output in the data_process.html file. (You can also get it in PDF form)