pip install -r requirements.txt

#Import libraries import pandas as pd #https://pandas.pydata.org/ import matplotlib.pyplot as plt #https://matplotlib.org/ import matplotlib.dates as mdates #https://matplotlib.org/ import numpy as np #http://www.numpy.org/ #from datetime import date #https://docs.python.org/3/library/datetime.html

#Read csv file using pandas #https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html ElectricityConsumption = pd.read_csv("cons.csv",dayfirst=True,sep=";", header=0,decimal=b",",index_col=0, parse_dates=True) ElectricityConsumption.info()

#Checking the table #ElectricityConsumption #Full table ElectricityConsumption.head() #Just a sample from "head()"

#Creating a basic plot using matplotlib plt.plot(ElectricityConsumption)

#Improving visualization ##### #https://matplotlib.org/api/_as_gen/matplotlib.pyplot.plot.html#matplotlib.pyplot.plot ##### #plot size plt.figure(figsize=(16,6)) #plot, defining color, marker and line style plt.plot(ElectricityConsumption,color='black', marker='.',linestyle='none') plt.title("Electricity consumption from 20.12.2017 - 30.6.2018") plt.ylabel("Energy in [kWh]") #y-axis label plt.grid(True) #grid plt.show() #show plot

#Information about specific periods ElectricityConsumption['2018-3'].info() #one month #ElectricityConsumption['2018-1':'2018-3'].info() #ranges months #ElectricityConsumption['2018-1-1':'2018-1-14'].info() #ranges days #ElectricityConsumption['2018-1-14 02:00:00':'2018-1-17 04:00:00'].info() #ranges hours

#Six months plt.figure(figsize=(16,6)) plt.plot(ElectricityConsumption['2018-1':'2018-6'],color='green', marker='.',linestyle='') plt.title("Electricity consumption from January to June, 2018") plt.ylabel("Energy in [kWh]") plt.grid(True) plt.show()

#One month plt.figure(figsize=(16,6)) plt.plot(ElectricityConsumption['2018-2'],color='black', marker='x',linestyle='') plt.title("Electricity consumption in Feb, 2018") plt.ylabel("Energy in [kWh]") plt.grid(True) plt.show()

#One day fig, ax = plt.subplots(1,figsize=(16,6)) plt.plot(ElectricityConsumption['2018-3-31'],color='black', marker='o',linestyle='--') plt.title("Electricity consumption in march 31, 2018") plt.ylabel("Energy in [kWh]") plt.grid(True) plt.tight_layout() #change x axis xfmt = mdates.DateFormatter('%H:%M') ax.xaxis.set_major_formatter(xfmt) plt.show()

#Plot two days #Day1 day1 = '2018-04-29' #Day2 day2 = '2018-05-01' #Difference delta = ElectricityConsumption[day2:].index[0].date() - ElectricityConsumption[day1:].index[0].date() # fig, ax = plt.subplots(1,figsize=(16,6)) # plt.plot(ElectricityConsumption[day1:day1], label=day1, color='black', marker='o',linestyle='--') plt.plot(ElectricityConsumption[day2:day2].index - pd.offsets.Day(delta.days), ElectricityConsumption[day2:day2].values, label=day2, color='blue', marker='x',linestyle='-') plt.legend() plt.ylim([0, 6]) plt.title("Electricity consumption") plt.ylabel("Energy in [kWh]") plt.grid(True) plt.tight_layout() #change x axis xfmt = mdates.DateFormatter('%H:%M') ax.xaxis.set_major_formatter(xfmt) # plt.show()

#Uploading the temperature from this day in Lappeenranta #http://en.ilmatieteenlaitos.fi/download-observations#!/ #Note parse_dates to combine the first columns, also note that the separator from #decimal is "." and data separator is "," Temperature = pd.read_csv("data-test.csv",dayfirst=True,sep=",", header=0,decimal=b".",index_col=0, parse_dates= [[0, 1, 2, 3]],usecols=[0,1,2,3,5]) Temperature.info()

#plotting plt.figure(figsize=(16,6)) plt.plot(Temperature,color='blue', marker='x',linestyle=':') plt.title("Air temperature in sep 7, 2013, at Lappeenranta airport station") plt.ylabel("Temperature in [°C]") plt.grid(True) plt.show()

Temperature2 = pd.read_csv("temp-20180429-LPR-airport.csv",dayfirst=True,sep=",", header=0,decimal=b".",index_col=0, parse_dates= [[0, 1, 2, 3]],usecols=[0,1,2,3,5]) Temperature2.info()

#plotting plt.figure(figsize=(16,6)) plt.plot(Temperature2['2018-4-29'],color='blue', marker='x',linestyle=':') plt.plot(Temperature2['2018-4-29'] > 11,color='black', marker='o',linestyle='') plt.title("Air temperature in April 29, 2018, at Lappeenranta airport station") plt.ylabel("Temperature in [°C]") plt.grid(True) plt.show()

#subplot function #https://matplotlib.org/2.0.1/examples/api/two_scales.html #### fig, ax1 = plt.subplots(figsize=(16,6)) #left axis ax1.set_ylabel("Energy in [kWh]", color='black') ax1.plot(ElectricityConsumption['2018-4-29'],color='black', marker='o',linestyle='--') ax1.plot(ElectricityConsumption['2018-4-29']>0.5,color='black', marker='o',linestyle='') #right axis ax2 = ax1.twinx() # instantiate a second axes that shares the same x-axis ax2.set_ylabel("Temperature in [°C]", color='blue',rotation=270,va="bottom") ax2.plot(Temperature2['2018-4-29'],color='blue', marker='x',linestyle=':') ax2.plot(Temperature2['2018-4-29']>5,color='blue', marker='x',linestyle='') # ax1.grid(True) plt.title("Electricity consumption and air temperature in April 29, 2018") #title #change x axis xfmt = mdates.DateFormatter('%H:%M') ax1.xaxis.set_major_formatter(xfmt) # plt.show() #NOTE the "1" is different in the different energy and the temperature plots (check scales)

#subplot function #https://matplotlib.org/2.0.1/examples/api/two_scales.html #### fig, ax1 = plt.subplots(figsize=(16,6)) #left axis ax1.set_ylabel("Energy in [kWh]", color='black') #ax1.plot(ElectricityConsumption['2018-4-29'],color='black', marker='o',linestyle='--') ax1.plot(ElectricityConsumption['2018-4-29']>0.2,color='red', marker='o',linestyle='') #right axis ax2 = ax1.twinx() # instantiate a second axes that shares the same x-axis ax2.set_ylabel("Temperature in [°C]", color='black',rotation=270,va="bottom") #ax2.plot(Temperature2['2018-4-29'],color='blue', marker='x',linestyle=':') ax2.plot(Temperature2['2018-4-29']>7,color='blue', marker='x',linestyle='') # ax1.grid(True) plt.title("Electricity consumption and air temperature in April 29, 2018") #title #change x axis xfmt = mdates.DateFormatter('%H:%M') ax1.xaxis.set_major_formatter(xfmt) # plt.show()

#plotting aux=(Temperature2['2018-4-29'].values>7) & (ElectricityConsumption['2018-4-29'].values>0.2) aux2=(Temperature2['2018-4-29'].values>7) | (ElectricityConsumption['2018-4-29'].values>0.2) plt.figure(figsize=(16,6)) #plt.plot(ElectricityConsumption['2018-4-29'].index, aux,color='black', marker='o',linestyle='') plt.plot(ElectricityConsumption['2018-4-29'].index, aux2, color='green', marker='s',linestyle='') plt.grid(True) plt.show()