Crunch.io Cube library
Project description
# crunch-cube
Open Source Python implementation of the API for working with Crunch Cubes
## Introduction
This package contains the implementation of the Crunch Cube API. It is used to extract useful information from Crunch Cube 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)
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
### 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
## Usage
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()
### Outputs: # # np.array([ # [5, 2], # [5, 3] # ])
## API
### as_array
Tabular, or matrix, representation of the _cube_. The detailed description can be found [here](http://crunch-cube.readthedocs.io/en/latest/cr.cube.html#cr-cube-crunch-cube-module).
### margin
Calculates margins of the _cube_. The detailed description can be found [here](http://crunch-cube.readthedocs.io/en/latest/cr.cube.html#cr-cube-crunch-cube-module).
### proportions
Calculates proportions of single variable elements to the whole sample size. The detailed description can be found [here](http://crunch-cube.readthedocs.io/en/latest/cr.cube.html#cr-cube-crunch-cube-module).
### percentages
Calculates percentages of single variable elements to the whole sample size. The detailed description can be found [here](http://crunch-cube.readthedocs.io/en/latest/cr.cube.html#cr-cube-crunch-cube-module).
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