<jupyter_start><jupyter_text>Daily Profiles<jupyter_code>#Error with bars and given by standard deviation
response = ug.plot_Daily_Profile_Error_Bars('SO2', ['Barcelona (Eixample)'], 'M', error = 'std', description=False)
#Error with bars and given by percentil 90
response = ug.plot_Daily_Profile_Error_Bars('SO2', ['Barcelona (Eixample)'], 'M', error = '90percentil', description=False)
#Error with area and given by percentil 90
response = ug.plot_Daily_Profile_Areas('SO2', ['Barcelona (Eixample)'], 'M', error = '90percentil', description=False)
#Plotting daily profile on all stations located in barcelona
response = ug.plot_Daily_Profile_Areas('SO2', ['Barcelona (Eixample)','Barcelona (Gràcia - Sant Gervasi)','Barcelona (Palau Reial)','Barcelona (Parc Vall Hebron)'], 'M', error = '90percentil', description=False)<jupyter_output><empty_output><jupyter_text>Time Series<jupyter_code>newdf = ug.plot_Time_Series_v1('SO2', 'Barcelona (Eixample)', 'M')
newdf = ug.plot_Time_Series_v1('SO2', 'Igualada', 'M')
newdf = ug.plot_Time_Series_v2('SO2', 'Barcelona (Eixample)', 'M')<jupyter_output><empty_output><jupyter_text>Headmaps<jupyter_code>## Stations versus days 
response = ug.plot_Matrix_Station_vs_Day('M', 'SO2')
response = ug.plot_Matrix_Station_vs_Hour('M', 'SO2')
response = ug.plot_Matrix_Day_vs_Hour('M', 'SO2')<jupyter_output><empty_output><jupyter_text>Correlation Observation vs predicted by Station<jupyter_code>ug.plot_Station_Correlation('M', 'SO2')<jupyter_output><empty_output>
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