From f99ecb11c11dbb9468e99e3f9c76cb9042a8cec5 Mon Sep 17 00:00:00 2001 From: Pritimay Sarkar Date: Sat, 11 Nov 2023 16:03:37 +0530 Subject: [PATCH] add new columns for download --- cloud-functions/python/functions/consolidation.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/cloud-functions/python/functions/consolidation.py b/cloud-functions/python/functions/consolidation.py index 84a5e22..1a2477f 100644 --- a/cloud-functions/python/functions/consolidation.py +++ b/cloud-functions/python/functions/consolidation.py @@ -74,7 +74,7 @@ def consolidation(request): df = df[(df['testTime'] > start_date) & (df['testTime'] <= end_date)] df = df.sort_values(by=['testTime'], ascending=False) # df = df.drop(['resultData', "reportUploadTime", "userImageURL", "testType", "birthYear", "testStatus", "reportPath", "createdBy", "csvPath", "result", "mobileId", "resultRatio", "localFlag", "led2", "led1"], axis=1) - df = df[["_id", "calculatedRatio", "deviceId", "deviceRatio", "kitSerial", "led1Average", "led1Buffer", "led1Sample", "led2Average", "led2Buffer", "led2Sample", "led3Average", "led3Buffer", "led3Sample", "led4Average", "led4Buffer", "led4Sample", "deviceSerialNumber", "name", "testTime", "classificationResult"]] + df = df[["_id", "calculatedRatio", "deviceId", "deviceRatio", "kitSerial", "led1Average", "led1Buffer", "led1Sample", "led2Average", "led2Buffer", "led2Sample", "led3Average", "led3Buffer", "led3Sample", "led4Average", "led4Buffer", "led4Sample", "deviceSerialNumber", "name", "testTime", "classificationResult", "abs427", "abs555", "predictedDenovixRatio", "prdClassification"]] df.rename(columns={'deviceSerialNumber': "loginId", "calculatedRatio": "calibratedRatio"}, inplace = True) df = df.reindex(sorted(df.columns), axis=1) df.to_excel(writer, sheet_name = 'data', index=False)