Skip to main content

Program to output the wearing time and other statistics of a Cambridge N99 | FFP2 mask.

Project description

Cambridge Masks Stats

Application to output the wearing time and other statistics of a Cambridge N99 | FFP2 mask.

the program is in the alpha phase. this means that the api will probably change often. the code is written in such a way that the syntax in the console is maintained or at least only minimal changes are made. this description also only deals with the terminal. the api will be described in the documentation of the code, if this is necessary. it is tried to write the code in a way that it is easy to understand.

the application is intended exclusively for the pro version of the cambridge mask, which should be worn for a maximum of 340 hours. the minutes are calculated automatically for aqi_level higher than 2, so that the wear is displayed correctly.

if there is no entry in the csv for a day between the start and end date, the time carried is automatically set to 0 for that day. this means that for months that lie between the start and end month <count_d> also counts the days for which the mask was not worn or for which there is no entry in the csv file.

requirements

python version

Python >= 3.6

dependencies

numpy==1.21.2
pandas==1.3.2
python-dateutil==2.8.2
pytz==2021.1
six==1.16.0

pip installation (with dependencies)

pip install cambridge-mask-stats

csv file

the CSV file to import needs the following header:

date,id,model,aqi_level,minutes_worn

  • date -> format yyyy-mm-dd
  • id -> mask id. preferably consecutive numbering
  • model -> mask model like 'The Churchill Pro'
  • aqi_level -> from 1-5 according to the data in the manual (1 = aqi below 50, 2 = 50 - 100 ...)
  • minutes_worn -> minutes worn on this date

execute

mask-stats <FILEPATH>

abbreviations in the output

  • count_d -> days in the month for which data are available
  • hrs -> hours (really worn)
  • mean_min_d -> mean minutes daily
  • pct -> percent | percentage (determined from sum_min_ratio)
  • sum_hrs -> summary hours
  • sum_min -> summary minutes
  • *_ratio -> values under consideration of the ratio (aqi_level > 2)

example

masks-stats /home/w01fdev/Documents/masks.csv

output

******************* StatsMasks *******************
worn | wear           hrs  hrs_ratio   pct
id model                                  
1  The Admiral Pro     10         12  3.53
2  The Churchill Pro   15         27  7.94

***************** StatsDateRange *****************
worn | wear  count_d  mean_min_d  mean_min_d_ratio  sum_min  sum_min_ratio  sum_hrs  sum_hrs_ratio   pct
2020-08-31         1          58                58       58             58        0              0  0.28
2020-09-30        30           9                18      278            563        4              9  2.76
2020-10-31        31          39                56     1237           1759       20             29  8.62

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

cambridge_mask_stats-0.8.0-py3-none-any.whl (19.2 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page