Welcome to Crunch Cube’s documentation!¶
Crunch Cube allows you to manipulate cube responses from the Crunch API using Python. We’ll refer to these cube responses as cubes in the subsequent text. When used in conjunction with pycrunch, this library can unlock powerful second-order analytics and visualizations.
A cube is obtained from the Crunch.io platform as a JSON response to a specific query created by a user. The most common usage is to obtain the following:
- Cross correlation between different variables
- Margins of the cross-tab cube
- Proportions of the cross-tab cube (e.g. proportions of each single element to the entire sample size)
Crunch Cube allows you to access these values from a cube response without dealing with the complexities of the underlying JSON format.
The data in a cube is often best represented in a table-like format. For this reason, many API methods return data as a numpy.ndarray object.
A quick example¶
After the cr.cube package has been successfully installed, the usage is as simple as:
>>> from cr.cube.cube import Cube
>>> ### Obtain the crunch cube JSON payload using app.crunch.io, pycrunch, rcrunch or scrunch
>>> ### And store it in the 'cube_JSON_response' variable
>>> cube = Cube(cube_JSON_response)
>>> print(cube)
Cube(name='MyCube', dimension_types='CAT x CAT')
>>> cube.counts
np.array([[1169, 547],
[1473, 1261]])
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.
