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new colummns for data download api

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This commit is contained in:
Pritimay Sarkar
2023-11-19 19:01:44 +05:30
parent c8e72681c0
commit 6379b018ef
1 changed files with 6 additions and 5 deletions
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11
scripts/consolidated_data.py
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@@ -9,6 +9,8 @@ import sys
import platform import platform
from datetime import datetime, timedelta from datetime import datetime, timedelta
environment = "af3cc"
if __name__ == "__main__": if __name__ == "__main__":
if platform.system() == 'Windows': if platform.system() == 'Windows':
@@ -16,7 +18,7 @@ if __name__ == "__main__":
else: else:
path_delim = '/' path_delim = '/'
key_file_path = os.getcwd() + path_delim + "keys" + path_delim + "hpos-preprod-firebase-adminsdk.json" key_file_path = os.getcwd() + path_delim + "keys" + path_delim + f"hpos-{environment}-firebase-adminsdk.json"
cred = credentials.Certificate(key_file_path) # Replace with your own service account key path cred = credentials.Certificate(key_file_path) # Replace with your own service account key path
firebase_admin.initialize_app(cred) firebase_admin.initialize_app(cred)
@@ -70,7 +72,7 @@ if __name__ == "__main__":
print(df.size) print(df.size)
# Save the DataFrame to a CSV file # Save the DataFrame to a CSV file
output_filename = f'data_{datetime.today().strftime("%d_%m_%Y_%H_%M")}.xlsx' output_filename = f'data_{environment}_{datetime.today().strftime("%d_%m_%Y_%H_%M")}.xlsx'
df.to_csv(output_filename, index=False) df.to_csv(output_filename, index=False)
downloads_dir = os.path.join(os.path.expanduser("~"), "Downloads") downloads_dir = os.path.join(os.path.expanduser("~"), "Downloads")
@@ -79,10 +81,9 @@ if __name__ == "__main__":
df = df[(df['testTime'] > start_date) & (df['testTime'] <= end_date)] df = df[(df['testTime'] > start_date) & (df['testTime'] <= end_date)]
df = df.sort_values(by=['testTime'], ascending=False) df = df.sort_values(by=['testTime'], ascending=False)
df = df[["_id", "calculatedRatio", "deviceId", "deviceRatio", "kitSerial", "led1Average", "led1Buffer", "led1Sample", "led2Average", "led2Buffer", "led2Sample", "deviceSerialNumber", "name", "testTime", "classificationResult", "resultData"]] df = df[["_id", "classificationResult", "prdClassification", "predictedDenovixRatio", "calculatedRatio", "deviceRatio", "kitSerial", "abs1", "led1Average", "led1Buffer", "led1Sample", "abs2", "led2Average", "led2Buffer", "led2Sample", "abs3", "led3Average", "led3Buffer", "led3Sample", "abs4", "led4Average", "led4Buffer", "led4Sample", "batteryLevel", "batteryVoltage", "deviceId", "deviceSerialNumber", "name", "testTime"]]
# df.rename(columns={'deviceSerialNumber': "login_id", "calculatedRatio": "calibrated_ratio", "led1Buffer": "427_buffer_intensity", "led2Buffer": "555_buffer_intensity", "led1Sample": "427_sample_intensity", "led2Sample": "555_sample_intensity", "led1Average": "427_absorbance", "led2Average": "555_absorbance"}, inplace = True) # df.rename(columns={'deviceSerialNumber': "login_id", "calculatedRatio": "calibrated_ratio", "led1Buffer": "427_buffer_intensity", "led2Buffer": "555_buffer_intensity", "led1Sample": "427_sample_intensity", "led2Sample": "555_sample_intensity", "led1Average": "427_absorbance", "led2Average": "555_absorbance"}, inplace = True)
# df = df.reindex(sorted(df.columns), axis=1)
df = df.reindex(sorted(df.columns), axis=1)
df.to_excel(writer, sheet_name = 'data', index=False) df.to_excel(writer, sheet_name = 'data', index=False)
writer.close() writer.close()