new kpi process

Author: Ubuntu

README.md

@@ -3,15 +3,30 @@ Purpose: to search and count anomalies in feature correlations for shops <br />
 Path on DS-instance: /home/ubuntu/DusFolder/anomaly_research/fea_conv/feature_anomaly_detection
 
 ## how to run main code
-change parameters in conv_config.py and run eshop_anomaly_count.py
+change parameters in conv_config.py and run eshop_anomaly_count.py <br />
+OR <br />
+change parameters in kpi_config.py and run eshop_anomaly_kpi.py <br />
 
 ### parameters
 
 ACCOUNT_ID - shop id <br />
-SLICE      - batch size in sessions  <br />
+SLICE      - batch size in sessions (for eshop_anomaly_count only) <br /> 
 BEG_DATE   - begin date of timeframe <br />
 END_DATE   - end date of timeframe <br />
 LQ         - left quantile aka bottom border for anomalies <br />
 RQ         - right quantile aka top border for anomalies <br />
 --to_sql   - key to export result to db <br />
---no_sql   - key to not export result to db (default)
+--no_sql   - key to not export result to db (default) <br />
+
+### result tables
+
+eshop_anomaly_count.py : <br />
+anomaly_matrix.csv <br />
+batch_counts.csv (sql data.feature_anomaly_batch_counts) <br />
+<br />
+eshop_anomaly_kpi.py : <br />
+anomaly_table.csv (sql data.eshop_anomaly_table) <br />
+metric_lines.csv <br />
+tops_kpi.csv (sql data.eshop_anomaly_tops_kpi) <br />
+
+