Crunch.io Cube library
Open Source Python implementation of the API for working with CrunchCubes
This package contains the implementation of the CrunchCube API. It is used to extract useful information from CrunchCube responses (we'll refer to them as cubes in the subsequent text). 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)
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.
cr.cube package can be installed by using the
pip install cr.cube
For development mode,
cr.cube needs to be installed from the local checkout
crunch-cube repository. It is strongly advised to use
Assuming you've created and activated a virtual environment
to the top-level folder of the repo, on the local file system, and run:
pip install -e .
python setup.py develop
To setup and run tests, you will need to install
cr.cube as well as testing
dependencies. To do this, from the root directory, simply run:
pip install -e .[testing]
And then tests can be run using
py.test in the root directory:
cr.cube package has been successfully installed, the usage is 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() ### Outputs: # # np.array([ # [5, 2], # [5, 3] # ])
Tabular, or matrix, representation of the cube. The detailed description can be found here.
Calculates margins of the cube. The detailed description can be found here.
Calculates proportions of single variable elements to the whole sample size. The detailed description can be found here.
Calculates percentages of single variable elements to the whole sample size. The detailed description can be found here.
index_tablefor MR (single element) x CAT
- fix second "broadcast error" bug (different cause)
- refactor to extract
_Measuresobject and related
- other general factoring improvements in
- fix "broadcast error" bug
- improve test coverage
- relocate test fixtures and add cached fixture lazy-loading
For a complete list of changes see history.
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