def get_sysprice_list(start_time, end_time, frequency='hourly'):
'''Wrapper function for creating pandas Series object from data
received from the database.
Returns: pandas Series object with Elspot daily system prices and
corresponding dates for predefined time period.
Parameters:
start_time - string representing the start of the time period,
format must be 'yyyy-mm-dd'.
end_time - string representing the end of the time period,
format must be 'yyyy-mm-dd'.
frequency - string representing the frequency of the output pandas
Series object. Currently must be one of ['hourly', 'daily']
'''
#Retrieve hourly system prices and timestamps from database as lists
_ , sys_prices, times = get_system_price_volume(start_time, end_time)
ts = Series(sys_prices, index=times)
if frequency == 'daily':
resampling_frequency = 'D'
if frequency == 'hourly':
#Resampling is not necessary
return ts
else:
return ts.resample(resampling_frequency, how='mean',
kind='timestamp')
def get_sysprice_list(start_time, end_time, frequency='hourly'):
'''Wrapper function for creating pandas Series object from data
received from the database.
Returns: pandas Series object with Elspot daily system prices and
corresponding dates for predefined time period.
Parameters:
start_time - string representing the start of the time period,
format must be 'yyyy-mm-dd'.
end_time - string representing the end of the time period,
format must be 'yyyy-mm-dd'.
frequency - string representing the frequency of the output pandas
Series object. Currently must be one of ['hourly', 'daily']
'''
#Retrieve hourly system prices and timestamps from database as lists
_ , sys_prices, times = get_system_price_volume(start_time, end_time)
ts = Series(sys_prices, index=times)
if frequency == 'daily':
resampling_frequency = 'D'
'''Weekly functionality not needed for now'''
'''elif frequency == 'weekly':
start_time = datetime.datetime.strptime(start_time, '%Y-%m-%d %H:%M:%S')
end_time = datetime.datetime.strptime(end_time, '%Y-%m-%d %H:%M:%S')
if start_time.date().weekday() != 0:
raise ValueError(str(start_time.date())+ " is a " + start_time.date().strftime('%A') + ". start_date must be a Monday.")
if end_time.date().weekday() != 6:
raise ValueError(str(end_time.date())+ " is a " + end_time.date().strftime('%A') + ". end_date must be a Sunday.")
resampling_frequency = 'W' '''
if frequency == 'monthly':
resampling_frequency = 'M'
if frequency == 'hourly':
#Resampling is not necessary
return ts
else:
return ts.resample(resampling_frequency, how='mean',
kind='timestamp')
