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bandicoot, an open-source python toolbox to analyze mobile phone metadata

An open-source python toolbox to analyze mobile phone metadata. July 1st, 2015. We released a new version (0.4) which includes new features, reporting variables, and supports ego-network analysis (e.g. clustering coefficient). This release is available on GitHub. Bandicoot 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. As well as Florent Robic...

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bandicoot, an open-source python toolbox to analyze mobile phone metadata | bandicoot.mit.edu Reviews
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An open-source python toolbox to analyze mobile phone metadata. July 1st, 2015. We released a new version (0.4) which includes new features, reporting variables, and supports ego-network analysis (e.g. clustering coefficient). This release is available on GitHub. Bandicoot 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. As well as Florent Robic...
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1 documentation
2 view on github
3 bandicoot
4 get started
5 test it
6 and pypi
7 easy to use environment
8 100 behavioral indicators
9 eg clustering coefficient
10 install bandicoot
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documentation,view on github,bandicoot,get started,test it,and pypi,easy to use environment,100 behavioral indicators,eg clustering coefficient,install bandicoot,pip install bandicoot,data visualization,for live examples,data verification,research papers
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bandicoot, an open-source python toolbox to analyze mobile phone metadata | bandicoot.mit.edu Reviews

https://bandicoot.mit.edu

An open-source python toolbox to analyze mobile phone metadata. July 1st, 2015. We released a new version (0.4) which includes new features, reporting variables, and supports ego-network analysis (e.g. clustering coefficient). This release is available on GitHub. Bandicoot 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. As well as Florent Robic...

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Quick start — bandicoot 0.5.0 documentation

http://bandicoot.mit.edu/docs/quickstart.html

Bandicoot 0.5.0 documentation. The easiest way to install it is using PyPI:. Alternatively, you can download it from here. Once unzipped you can either import it. Bandicoot takes one file per user and assume that all user records are in the provided directory. Will load records for the user. And will load antennas from the file. Optionally, bandicoot can also load a file containing attributes. Bandicoot uses one record file per user. Record files are structured as follows:. Load a sample user. Percent ou...

2

bandicoot, an open-source python toolbox to analyze mobile phone metadata — bandicoot 0.5.0 documentation

http://bandicoot.mit.edu/docs

Bandicoot 0.5.0 documentation. Bandicoot, an open-source python toolbox to analyze mobile phone metadata. Bandicoot, an open-source python toolbox to analyze mobile phone metadata. Is an open-source python toolbox to analyze and extract behavioral indicators from mobile phone data. It is developed by Yves-Alexandre de Montjoye. At the MIT Media Lab. The behavioral indicators computed by bandicoot have already been used to release data as part of Orange D4D Challenge. To predict gender, age.

3

demo

http://bandicoot.mit.edu/demo

Bandicoot notebook ¶. Is an open-source python toolbox to analyze mobile phone metadata. For more information, see: http:/ bandicoot.mit.edu/. You can download this notebook on Github from our repository at github.com/yvesalexandre/bandicoot. Try bandicoot on your phone! If you want to try bandicoot with your own data, download our Android app at bandicoot.mit.edu/android. Input files ¶. Records for the user ego. GPS locations of cell towers. Loading a user ¶. No attribute stored [x]. The signature of the.

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bandicoot, an open-source python toolbox to analyze mobile phone metadata

An open-source python toolbox to analyze mobile phone metadata. July 1st, 2015. We released a new version (0.4) which includes new features, reporting variables, and supports ego-network analysis (e.g. clustering coefficient). This release is available on GitHub. Bandicoot 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. As well as Florent Robic...

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