| | 1 | = S3Cube = |
| | 2 | |
| | 3 | S3Cube is a REST method handler for data analysis. |
| | 4 | |
| | 5 | == Functionality == |
| | 6 | |
| | 7 | S3Cube can generate contingency tables (a.k.a. pivot tables) from S3Resources. |
| | 8 | |
| | 9 | == Dependencies == |
| | 10 | |
| | 11 | S3Cube uses pyvttbl to generate contingency tables. A modified version of pyvttbl is integrated into the S3 framework. |
| | 12 | |
| | 13 | Pyvttbl requires the following Python modules: |
| | 14 | |
| | 15 | - scipy |
| | 16 | - numpy |
| | 17 | - matplotlib |
| | 18 | |
| | 19 | Python 2.7 is recommended for S3Cube, however it would work with Python 2.6. |
| | 20 | |
| | 21 | == URL methods == |
| | 22 | |
| | 23 | S3Cube responds to the analyze URL method. |
| | 24 | |
| | 25 | The following parameters are accepted: |
| | 26 | |
| | 27 | ||Parameter||Explanation||required?|| |
| | 28 | ||rows||the name of the field to be used for the table rows||yes|| |
| | 29 | ||cols||the name of the field to be used for the table columns||yes|| |
| | 30 | ||fact||the name of the field to be used for the instance values||yes|| |
| | 31 | ||aggregate||the aggregation function||no|| |
| | 32 | |
| | 33 | S3Cube supports a number of aggregation functions. The following functions have been tested so far: |
| | 34 | |
| | 35 | ||Function||Explanation|| |
| | 36 | ||list||a comma-separated list of all instance values|| |
| | 37 | ||count||the number of instance values|| |
| | 38 | ||sum||the sum of all instance values|| |
| | 39 | ||avg||the average (mean) of all instance values|| |
| | 40 | |
| | 41 | == Further Development == |
| | 42 | |
| | 43 | The following enhancements are currently under development: |
| | 44 | |
| | 45 | - Totals row and column |
| | 46 | - Support for JSON, CSV and XLS exports |
| | 47 | - Support for client-side graphs representation (via JSON) |
| | 48 | |
