smiuser/hpos-data
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

modify to show user name

Browse Source
This commit is contained in:
Pritimay Sarkar
2024-01-24 17:40:36 +05:30
parent 56ea6a3433
commit 662b235208
2 changed files with 23 additions and 6 deletions
Download Patch File Download Diff File Expand all files Collapse all files

6
cloud-functions/python/functions/consolidation/requirements.txt Normal file
View File

@@ -0,0 +1,6 @@
functions-framework==3.*
firebase_functions~=0.1.0
pandas==2.0.3
openpyxl==3.1.2
firebase-admin==6.2.0
google-cloud-firestore==2.14.0

23
scripts/consolidated_data.py
View File

@@ -9,7 +9,7 @@ import sys
import platform
from datetime import datetime, timedelta
environment = "af3cc"
environment = "qa"
if __name__ == "__main__":
@@ -67,11 +67,22 @@ if __name__ == "__main__":
data.append(test_data)
# Convert the data to a DataFrame
df = pd.DataFrame(data)
print(df)
test_df = pd.DataFrame(data)
print(test_df)
print(test_df.columns)
query = db.collection("patientData").where(filter=FieldFilter("createdAt", ">=", start_date)).where(filter=FieldFilter("createdAt", "<", end_date))
data = []
docs = query.stream()
for doc in docs:
row_data = doc.to_dict()
data.append(row_data)
user_df = pd.DataFrame(data)
df = pd.merge(test_df, user_df, on='_id')
print(df.columns)
# Save the DataFrame to a CSV file
output_filename = f'data_{environment}_{datetime.today().strftime("%d_%m_%Y_%H_%M")}.xlsx'
df.to_csv(output_filename, index=False)
@@ -82,7 +93,7 @@ if __name__ == "__main__":
df = df[(df['testTime'] > start_date) & (df['testTime'] <= end_date)]
df = df.sort_values(by=['testTime'], ascending=False)
column_names = ["_id", "classificationResult", "deviceRatioClass", "prdClassification", "slopeRatioClass", "predictedDenovixRatio", "slopeRatio", "calculatedRatio", "deviceRatio", "kitSerial", "led1Gain1", "led1Gain2", "led1Gain4", "abs1", "led1Average", "led1Buffer", "led1Sample", "led2Gain1", "led2Gain2", "led2Gain4", "abs2", "led2Average", "led2Buffer", "led2Sample", "led3Gain1", "led3Gain2", "led3Gain4", "hb3", "abs3", "led3Average", "led3Buffer", "led3Sample", "led4Gain1", "led4Gain2", "led4Gain4", "hb4", "abs4", "led4Average", "led4Average", "led4Buffer", "led4Sample", "batteryLevel", "batteryVoltage", "solution", "concentration", "volume", "errorMessages", "deviceId", "deviceSerialNumber", "appVersion", "name", "testTime"]
column_names = ["_id", "classificationResult", "deviceRatioClass", "prdClassification", "slopeRatioClass", "predictedDenovixRatio", "slopeRatio", "calculatedRatio", "deviceRatio", "kitSerial", "led1Gain1", "led1Gain2", "led1Gain4", "abs1", "led1Average", "led1Buffer", "led1Sample", "led2Gain1", "led2Gain2", "led2Gain4", "abs2", "led2Average", "led2Buffer", "led2Sample", "led3Gain1", "led3Gain2", "led3Gain4", "hb3", "abs3", "led3Average", "led3Buffer", "led3Sample", "led4Gain1", "led4Gain2", "led4Gain4", "hb4", "abs4", "led4Average", "led4Average", "led4Buffer", "led4Sample", "batteryLevel", "batteryVoltage", "solution", "concentration", "volume", "errorMessages", "deviceId", "deviceSerialNumber", "appVersion", "name_y", "testTime"]
common_columns = [col for col in column_names if col in df.columns]
df = df[common_columns]