Crunch.io Cube library

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for earbitrio from gravatar.com earbitrio Avatar for gergness from gravatar.com gergness Avatar for operation from gravatar.com operation Avatar for percious from gravatar.com percious Avatar for slobodan.ilic from gravatar.com slobodan.ilic

Unverified details

These details have not been verified by PyPI
Project links
Meta
Classifiers

Project description

crunch-cube

Open Source Python implementation of the API for working with CrunchCubes

Introduction

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)
  • 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 cr.cube package can be installed by using the pip install:

pip install cr.cube

For developers

For development mode, cr.cube needs to be installed from the local checkout of the crunch-cube repository. It is strongly advised to use virtualenv. Assuming you've created and activated a virtual environment venv, navigate to the top-level folder of the repo, on the local file system, and run:

pip install -e .

or

python setup.py develop

Running tests

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:

pytest

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.

margin

Calculates margins of the cube. The detailed description can be found here.

proportions

Calculates proportions of single variable elements to the whole sample size. The detailed description can be found here.

percentages

Calculates percentages of single variable elements to the whole sample size. The detailed description can be found here.

Build Status Coverage Status Documentation Status

Changes

2.3.2

  • Allow hiding MR insertions

2.3.1

  • Consolidate weighted counts
  • Fix bug with weighted counts for numeric arrays

2.3.0

  • Consolidation of weighted counts such that bases are no longer calculated by adding across subvariables.
  • Removed the _Slice.table_margin_unpruned property, instead use _Slice.table_margin_range to get the unpruned range of table margins.

2.2.3

  • More sort-by-value support including a fallback to payload order

For a complete list of changes see history.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for earbitrio from gravatar.com earbitrio Avatar for gergness from gravatar.com gergness Avatar for operation from gravatar.com operation Avatar for percious from gravatar.com percious Avatar for slobodan.ilic from gravatar.com slobodan.ilic

Unverified details

These details have not been verified by PyPI
Project links
Meta
Classifiers

Release history Release notifications | RSS feed

3.0.45

3.0.44

3.0.43

3.0.42

3.0.41

3.0.40

3.0.39

3.0.38

3.0.37

3.0.36

3.0.35

3.0.34

3.0.33

3.0.32

3.0.31

3.0.30

3.0.29

3.0.28

3.0.27

3.0.26

3.0.25

3.0.24

3.0.23

3.0.22

3.0.21

3.0.20

3.0.19

3.0.18

3.0.17

3.0.16

3.0.15

3.0.14

3.0.13

3.0.12

3.0.11

3.0.10

3.0.9

3.0.8

3.0.7

3.0.6

3.0.5

3.0.4

3.0.3

3.0.2

3.0.1

3.0.0

2.3.9

2.3.8

2.3.7

2.3.6

2.3.5

2.3.4

2.3.3

This version

2.3.2

2.3.1

2.3.0

2.2.3

2.2.2

2.2.1

2.2.0

2.1.34

2.1.33

2.1.32

2.1.31

2.1.30

2.1.29

2.1.28

2.1.27

2.1.26

2.1.25

2.1.24

2.1.23

2.1.22

2.1.21

2.1.20

2.1.19

2.1.18

2.1.17

2.1.16

2.1.15

2.1.14

2.1.13

2.1.12

2.1.11

2.1.10

2.1.9

2.1.8

2.1.7

2.1.6

2.1.5

2.1.4

2.1.3

2.1.2

2.1.1

2.1.0

2.0.3

2.0.2

2.0.1

2.0.0

1.12.11

1.12.11rc0 pre-release

1.12.11b0 pre-release

1.12.10

1.12.9

1.12.8

1.12.7

1.12.6

1.12.5

1.12.4

1.12.4b0 pre-release

1.12.3

1.12.2

1.12.1

1.12.1a0 pre-release

1.12.0a0 pre-release

1.11.37

1.11.36

1.11.35

1.11.34

1.11.33

1.11.32

1.11.31

1.11.30

1.11.29

1.11.28

1.11.27

1.11.26

1.11.25

1.11.24

1.11.23

1.11.22

1.11.21

1.11.20

1.11.19

1.11.18

1.11.17

1.11.16

1.11.15

1.11.14

1.11.13

1.11.12

1.11.11

1.11.10

1.11.9

1.11.8

1.11.7

1.11.6

1.11.5

1.11.4

1.11.3

1.11.2

1.11.1

1.11.0

1.10.6

1.10.5

1.10.4

1.10.3

1.10.2

1.10.1

1.10.0

1.9.19

1.9.18

1.9.17

1.9.16

1.9.15

1.9.14

1.9.13

1.9.12

1.9.11

1.9.10

1.9.9

1.9.8

1.9.7

1.9.6

1.9.5

1.9.4

1.9.3

1.9.2

1.9.1

1.9.0

1.8.6

1.8.5

1.8.4

1.8.3

1.8.2

1.8.1

1.8.0

1.7.3

1.7.2

1.7.0

1.6.11

1.6.10

1.6.8

1.6.7

1.6.6

1.6.5

1.6.3

1.6.1

1.6.0

1.5.6

1.5.3

1.5.2

1.5.1

1.5.0

1.4.5

1.4.4

1.4.3

1.4.2

1.4.1

1.4

1.3

1.2

1.1

1.0

0.1

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

cr.cube-2.3.2.tar.gz (1.1 MB view details)

Uploaded Source

Built Distribution

cr.cube-2.3.2-py3-none-any.whl (338.0 kB view details)

Uploaded Python 3

File details

Details for the file cr.cube-2.3.2.tar.gz.

File metadata

  • Download URL: cr.cube-2.3.2.tar.gz
  • Upload date:
  • Size: 1.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.6.1 requests/2.21.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.56.0 CPython/3.8.0

File hashes

Hashes for cr.cube-2.3.2.tar.gz
Algorithm Hash digest
SHA256 cd9dadd0e8dec3e6c440496fd15a36baf41058382fcadbe95db1a9c9e0712db0
MD5 121e9d5c862216f8111be54162b01be6
BLAKE2b-256 02a9b07d3792a4bdaeeb520b6abd5bdd5764efd182a7fcdcbd014b0e2244643a

See more details on using hashes here.

File details

Details for the file cr.cube-2.3.2-py3-none-any.whl.

File metadata

  • Download URL: cr.cube-2.3.2-py3-none-any.whl
  • Upload date:
  • Size: 338.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.6.1 requests/2.21.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.56.0 CPython/3.8.0

File hashes

Hashes for cr.cube-2.3.2-py3-none-any.whl
Algorithm Hash digest
SHA256 b7bc5e0346e6e2153deb7c64fde9be506d7d6a7861163428dd9c860b532792c8
MD5 427024a031175886d97a48e46fbfa9c0
BLAKE2b-256 efb5a23f1a5d68355b280f9c3e79c879f5f3fe2c5243f008781c45ba962ae126

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page