task one is mostly done

problemareascron.py

@@ -44,7 +44,7 @@
 # writes to a new csv file, so we can use pandas on the real-time data
 
 # this file location ALSO ONLY WORKS ON THE SERVER --->
-with open('/media/ea/Data/Students/jade/buildingEnergyApi/ahs_air_data.csv', mode='a') as ahs_air_data:
+with open('/media/ea/Data/Students/jade/buildingEnergyApi/ahs_air_data.csv', mode='w') as ahs_air_data:
     temp_writer = csv.writer(ahs_air_data, delimiter=";")
     # Iterate over the rows of the dataframe, displaying temperature and CO2 values extracted from map
     for index, row in df.iterrows():

task_one.py

@@ -4,4 +4,107 @@
 import pandas as pd
 import sqlite3
 
+# Copyright 2018 Building Energy Gateway.  All rights reserved.
 
+import time
+from building_data_requests import get_bulk
+import numbers
+import csv
+from crontab import CronTab
+
+start_time = time.time()
+
+# Read spreadsheet into a dataframe.
+# Each row contains the following:
+#   - Label
+#   - Facility
+#   - Instance ID of CO2 sensor
+#   - Instance ID of temperature sensor
+
+#/media/ea/Data/Students/jade/buildingEnergyApi/
+df = pd.read_csv('ahs_air.csv', na_filter=False, comment='#' )
+# This file location doesn't work on the server (see above file path) --> be careful
+
+# Initialize empty bulk request
+bulk_rq = []
+
+# Iterate over the rows of the dataframe, adding elements to the bulk request
+for index, row in df.iterrows():
+
+    # Append facility/instance pairs to bulk request
+    if row['Temperature']:
+        bulk_rq.append( { 'facility': row['Facility'], 'instance': row['Temperature'] } )
+    if row['CO2']:
+        bulk_rq.append( { 'facility': row['Facility'], 'instance': row['CO2'] } )
+
+# Issue get-bulk request
+bulk_rsp = get_bulk( bulk_rq )
+
+# Extract map from get-bulk response
+map = bulk_rsp['rsp_map']
+
+# Output column headings
+# print( 'Location,Temperature,Temperature Units,CO2,CO2 Units' )
+
+# writes to a new csv file, so we can use pandas on the real-time data
+
+# this file location ALSO DOESN'T WORK ON THE SERVER ---> add in that path /media/ea/Data/Students/jade/buildingEnergyApi/
+with open('ahs_air_data.csv', mode='w') as ahs_air_data:
+    temp_writer = csv.writer(ahs_air_data, delimiter=";")
+    # Iterate over the rows of the dataframe, displaying temperature and CO2 values extracted from map
+    for index, row in df.iterrows():
+
+        # Initialize empty display values
+        temp_value = ''
+        temp_units = ''
+        co2_value = ''
+        co2_units = ''
+
+        # Get facility of current row
+        facility = row['Facility']
+
+        # Try to extract current row's temperature and CO2 values from map
+        if facility in map:
+
+            instance = str( row['Temperature'] )
+            if instance and ( instance in map[facility] ):
+                rsp = map[facility][instance]
+                property = rsp['property']
+                temp_value = int( rsp[property] ) if isinstance( rsp[property], numbers.Number ) else ''
+                temp_units = rsp['units']
+
+            instance = str( row['CO2'] )
+            if instance and ( instance in map[facility] ):
+                rsp = map[facility][instance]
+                property = rsp['property']
+                co2_value = int( rsp[property] ) if isinstance( rsp[property], numbers.Number ) else ''
+                co2_units = rsp['units']
+
+        # Output CSV format
+        # print(time.asctime())
+        current_time = time.asctime()
+        temp_writer.writerow( ['{0},{1},{2},{3},{4},{5}'.format( current_time, row['Label'], temp_value, temp_units, co2_value, co2_units ) ])
+        #instead of printing, uses writerow method to enter into the csv file
+
+ahs_air_data.close()
+
+PATH = 'my_file'#change for the server
+
+df = pd.read_csv('ahs_air_data.csv', names=['Timestamp', 'Room #', 'Temperature', 'Temp. Units', 'CO2', 'CO2 Units']).set_index('Room #')
+
+engine = sqlalchemy.create_engine('sqlite:///' + PATH)
+
+conn = sqlite3.connect(PATH)
+df.to_sql("ProblemAreasDatabase", conn)
+new_df = pd.read_sql_table("ProblemAreasDatabase", engine)
+
+print(new_df)
+
+'''
+right now, it needs me to define a new table name every time...
+
+sql = 'DELETE FROM ProblemAreasDatabase'
+cur = conn.cursor()
+cur.execute(sql)
+conn.commit()
+'''