hiplab/privacykit
hiplab
/
privacykit
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Update 'README.md'

This commit is contained in:
steve 2018-09-27 10:49:19 -05:00
parent 991a3cb6c9
commit 4df27a251c
1 changed files with 5 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

7
README.md
View File

@ -7,7 +7,7 @@ This project is intended to compute an estimated value of risk for a given datab
3. Compute risk via SQL using group by
## Python environment
The following are the dependencies needed to run the code:
The following are the dependencies needed to run the code:
pandas
numpy
@ -17,16 +17,17 @@ This project is intended to compute an estimated value of risk for a given datab
## Usage
*Generate The merged dataset
**Generate The merged dataset**
python risk.py create --i_dataset <in dataset|schema> --o_dataset <out dataset|schema> --table <name> --path <bigquery-key-file> --key <patient-id-field-name> [--file ]
* * Compute risk (marketer, prosecutor)
**Compute risk (marketer, prosecutor)**
python risk.py compute --i_dataset <dataset> --table <name> --path <bigquery-key-file> --key <patient-id-field-name>
## Limitations
- It works against bigquery for now
@TODO:
- Need to write a transport layer (database interface)
- Support for referential integrity, so one table can be selected and a dataset derived given referential integrity