Welcome to Crunch Cube’s documentation!¶
The purpose of this library is to make it much easier to manipulate cube responses that come from the crunch api. (we’ll refer to them as _cubes_ in the subsequent text). When used in conjunction with pycrunch, this library can unlock powerful second-order analytics and visualizations.
_Cubes_ are obtained from the Crunch.io platform, as JSON responses to the specific _queries_ created by the user. These queries specify which data the user wants to extract from the Crunch.io system. The most common usage is to obtain the following:
- Cross correlation between different variable
- Margins of the cross tab _cube_
- Proportions of the cross tab _cube_ (e.g. proportions of each single element to the entire sample size)
- Percentages
When the data is obtained from the Crunch.io platform, it needs to be interpreted to the form that’s convenient for a user. The actual shape of the _cube_ JSON contains many internal details, which are not of essence to the end-user (but are still necessary for proper _cube_ functionality).
The job of this library is to provide a convenient API that handles those intricacies, and enables the user to quickly and easily obtain (extract) the relevant data from the _cube_. Such data is best represented in a table-like format. For this reason, the most of the API functions return some form of the ndarray type, from the numpy package. Each function is explained in greater detail, uner its own section, under the API subsection of this document.
Installation¶
The Crunch Cube package can be installed by using the pip install:
`
pip install cr.cube
`
A quick example¶
After the cr.cube package has been successfully installed, the usage is as simple as:
>>> from cr.cube.crunch_cube import CrunchCube
>>> ### Obtain the crunch cube JSON from the Crunch.io
>>> ### And store it in the 'cube_JSON_response' variable
>>> cube = CrunchCube(cube_JSON_response)
>>> cube.as_array()
np.array([
[5, 2],
[5, 3]
])
For developers¶
- For development mode, Crunch Cube needs to be installed from the local checkout of the crunch-cube repository.
- Navigate to the top-level folder of the repo, on the local file system, and run:
`
$ python setup.py develop
$ py.test tests -cov=cr.cube
`
Note that we are happy to accept pull requests, please be certain that your code has proper coverage before submitting. All pull requests will be tested by travis.
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