Skip to main content

bandicoot

Version MIT License PyPI downloads Continuous integration

bandicoot (http://bandicoot.mit.edu) is Python toolbox to analyze mobile phone metadata. It provides a complete, easy-to-use environment for data-scientist to analyze mobile phone metadata. With only a few lines of code, load your datasets, visualize the data, perform analyses, and export the results.

Bandicoot interactive visualization

Where to get it

The source code is currently hosted on Github at https://github.com/computationalprivacy/bandicoot. Binary installers for the latest released version are available at the Python package index:

http://pypi.python.org/pypi/bandicoot/

And via easy_install:

easy_install bandicoot

or pip:

pip install bandicoot

Dependencies

bandicoot has no dependencies, which allows users to easily compute indicators on a production machine. To run tests and compile the visualization, optional dependencies are needed:

Licence

MIT

Documentation

The official documentation is hosted on http://bandicoot.mit.edu/docs. It includes a quickstart tutorial, a detailed reference for all functions, and guides on how to use and extend bandicoot. You can also check out our interactive training notebooks to learn how to download your own data from your mobile phone and load it into bandicoot to visualize it or to learn how to use bandicoot indicators in scikit-learn.

Metadata

Release files for bandicoot 0.6.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for bandicoot 0.6.0
File Size Uploaded
bandicoot-0.6.0.tar.gz 492.3 kB Details

Release files / bandicoot-0.6.0.tar.gz

Download URL bandicoot-0.6.0.tar.gz
Size 492.3 kB
Tags Source
SHA-256 checksum
How to use checksums
99e5eb50db6d7ddc7d0904cfd89f499ee560caca9d1cb6a2f8e835920f113d6e
BLAKE2b-256 checksum
How to use checksums
0823c3867bada3de8d9dc6a24331e997192fd84375c81d3eccab6d363ee79499
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.4.0.post20200518 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.7.7

Release history Release notifications | RSS feed

This release

0.6.0 This release

1 release file

0.5.3

1 release file

0.5.2

1 release file

0.5.1

1 release file

0.5

1 release file

0.4.0

1 release file

0.3.0

1 release file

0.2.3

1 release file

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page