Skip to main content

This is used for analyzing the obtain from IoT AirQo devices

Project description

AirQloud Analysis

A Python library for analyzing data from IoT AirQo devices to provide insights on sensor health, device uptime, data completeness, and more.

Installation

pip install airqloudanalysis

Features

  • Sensor health analysis
  • Device uptime monitoring
  • Data completeness metrics
  • Battery performance analysis
  • Support for device-specific and AirQloud-level analysis

Usage

import airqloudanalysis as aqa

# Initialize with your API token
token = "your_api_token"
for google sheets
file_path = "file path"

airQlouds = ["Kampala", "Nairobi"]
or 
deviceNames = ['aq_g4_95', 'aq_23']

start = "2023-01-01"
end = "2023-01-31"
maintenenceDate = date(2025, 3, 1)


# Get device data
df = aqa.airqloudlist_api(token, airQlouds)

# Process data for the specified date range
processed_data = aqa.process_data(df, start, end)

# Calculate uptime
uptime_data = aqa.calculate_uptime(processed_data, start, end)

# Create summary
device_time_diff = aqa.timeLastPost(df)
summary = aqa.create_summary_df(df, device_time_diff, uptime_data)

# Generate reports
summary_report = aqa.export_summary_csv_api(summary, airQlouds, [])

Noticable changes to this library

Library version change The library version holds various changes to the following functions;

Calculate_uptime

Altered to use start and end date to fill in the null while computing the collective uptime and now takes in two extra parameters: start and end date Function call is calculate_uptime(dataframe df, string start, string end)

Online devices list

This provides a variation of the timeLastPost function providing a list of online devices, their device numbers, time difference, and the airqlouds they belong to Function call is onlineDeviceList(dataframe df):

Offline devices list

This provides a variation of the timeLastPost function providing a list of offline devices, their device numbers, time difference, and the airqlouds they belong to Function call is offlineDeviceList(dataframe df):

Full Documentation

For complete documentation and examples, please visit: https://docs.google.com/document/d/1Dc4zQceYjoXDwmHKy99hp7x49kq8LtoSAXBA-1HMwA4/edit?usp=sharing

The repository for this library https://github.com/OlukaGibson/deviceAnalysisLibrary.git

License

This project is licensed under the terms of the license included in the repository.

Author

Project details


Download files

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

Source Distribution

airqloudanalysis-0.0.731.tar.gz (21.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

airqloudanalysis-0.0.731-py3-none-any.whl (20.3 kB view details)

Uploaded Python 3

File details

Details for the file airqloudanalysis-0.0.731.tar.gz.

File metadata

  • Download URL: airqloudanalysis-0.0.731.tar.gz
  • Upload date:
  • Size: 21.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.3

File hashes

Hashes for airqloudanalysis-0.0.731.tar.gz
Algorithm Hash digest
SHA256 a6e842de2b9e09b97d661624a938ab1ee1e38bcd4d76797148551a221ba56130
MD5 e504007fb886dcf47568d82bed32e6f8
BLAKE2b-256 c3aff3b2ad58c28e854f621af4ee7faf37816ad00cf1a963e3963eac366f7d16

See more details on using hashes here.

File details

Details for the file airqloudanalysis-0.0.731-py3-none-any.whl.

File metadata

File hashes

Hashes for airqloudanalysis-0.0.731-py3-none-any.whl
Algorithm Hash digest
SHA256 c5192ac228204dc03683615ea32e4373593bd7c2a79785e39a6ec4c0ac44d805
MD5 79700c5646897b7144d34d93827d3b18
BLAKE2b-256 bfe3591fb384700027d632ed0a00efc654b2ef2679ad0e578153bfd372cf7caf

See more details on using hashes here.

Supported by

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