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).
[](https://travis-ci.org/Crunch-io/crunch-cube)
[](https://coveralls.io/github/Crunch-io/crunch-cube?branch=master)
[](http://crunch-cube.readthedocs.io/en/latest/?badge=latest)
## Changes
1.0 Initial release
1.1 *Fix stray ipdb.
1.2 Support exporter
1.3 Implement Headers & Subtotals
1.4 Update based on tabbook tests from `cr.lib`
1.4.1 Update based on deck tests from `cr.server`
1.4.2 Fix bugs discovered by first `cr.exporter` deploy to alpha
1.4.3 Fix bug (exporting 2D crtab with H&S on row only)
1.4.4 Implement obtaining labels with category ids (useful for H&S in exporter)
1.4.5 Fix MR x MR proportions calculation
1.5.0 Start implementing index table functionality
1.5.1 Implement index for MR x MR
1.5.2 Fix bugs with `anchor: 0` for H&S
1.5.3 Fix bugs with invalid input data for H&S
1.6.0 Z-Score and bug fixes.
1.6.1 standardized_residuals are now included.
1.6.2 support "Before" and "After" in variable transformations since they exist in zz9 data.
1.6.4 Fixes for 3d Pruning.
1.6.5 Fixes for Pruning and Headers and subtotals.
Population size support.
Fx various calculations in 3d cubes.
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).
[](https://travis-ci.org/Crunch-io/crunch-cube)
[](https://coveralls.io/github/Crunch-io/crunch-cube?branch=master)
[](http://crunch-cube.readthedocs.io/en/latest/?badge=latest)
## Changes
1.0 Initial release
1.1 *Fix stray ipdb.
1.2 Support exporter
1.3 Implement Headers & Subtotals
1.4 Update based on tabbook tests from `cr.lib`
1.4.1 Update based on deck tests from `cr.server`
1.4.2 Fix bugs discovered by first `cr.exporter` deploy to alpha
1.4.3 Fix bug (exporting 2D crtab with H&S on row only)
1.4.4 Implement obtaining labels with category ids (useful for H&S in exporter)
1.4.5 Fix MR x MR proportions calculation
1.5.0 Start implementing index table functionality
1.5.1 Implement index for MR x MR
1.5.2 Fix bugs with `anchor: 0` for H&S
1.5.3 Fix bugs with invalid input data for H&S
1.6.0 Z-Score and bug fixes.
1.6.1 standardized_residuals are now included.
1.6.2 support "Before" and "After" in variable transformations since they exist in zz9 data.
1.6.4 Fixes for 3d Pruning.
1.6.5 Fixes for Pruning and Headers and subtotals.
Population size support.
Fx various calculations in 3d cubes.
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