def set_accuracy_data(self):
"""
Set up accuracy data for one hotel
"""
if self.department_accuracy_data is None:
dep_have_revenue_data = self.get_list_dept(
has_revenue=True, no_include_hotel_id=False)
l_df = []
for dep_id in dep_have_revenue_data:
try:
dep_acc_data = self.db.get_department_forecast_accuracy_data(
self.client_id, dep_id, ACCURACY_LEADTIME)
except:
log.warning('%s:%s %s:%s Cannot_get_accuracy_data:1' %
(col_name.CLIENT, self.client_id,
col_name.DEPT_ID, dep_id))
continue
if not dep_acc_data:
log.warning('%s:%s %s:%s Cannot_get_accuracy_data:1' %
(col_name.CLIENT, self.client_id,
col_name.DEPT_ID, dep_id))
# dep_acc_data = pd.DataFrame(dep_acc_data, index=[0])
# dep_acc_data['H_Id'] = dep_id
#mm
dep_acc_data = pd.DataFrame(dep_acc_data)
dep_acc_data = dep_acc_data[dep_acc_data['H_Id'] == dep_id]
l_df.append(dep_acc_data)
self.department_accuracy_data = pd.concat(l_df, ignore_index=True)
def create_season_df(self, json_data):
"""
Using d2o api to get season data.
Returns:
pd.DataFrame: season data in dataframe format
|Id|From|To|Names|Color
"""
try:
l_df = []
for period in json_data['Periods']:
if period['Dates'] == []:
continue
else:
df = pd.DataFrame(period['Dates'])
df['Color'] = period['Color']
df['Names'] = period['Name']
df['From'] = pd.to_datetime(df['From'])
df['To'] = pd.to_datetime(df['To'])
df = df[['Id', 'From', 'To', 'Names', 'Color']]
l_df.append(df)
from_to_ss_df = pd.concat(l_df, ignore_index=True)
from_to_ss_df = from_to_ss_df[from_to_ss_df.Color != '#000000']
return from_to_ss_df
except Exception, e:
log.warning('No_season_data')
return None
def set_hotel_total_data(self):
"""
if hotel total data (total is a special kind of department data) set up hotel_total_data as
dataframe follows structure bellow:
Date | DepId | Guest | Unit | Revenue | FoodRevenue | TotalFoodRevenue
"""
if self.hotel_total_data is None:
data_in_json = self.db.get_hotel_food_revenue_in_a_specific_time_period(
self.client_id, self.hotel_id, self.from_date, self.to_date)
if len(data_in_json) > 0:
total_rev_food_df = pd.DataFrame(data_in_json)
total_rev_food_df['Date'] = pd.to_datetime(
total_rev_food_df['Date'])
total_rev_food_df.set_index('Date', inplace=True)
self.hotel_total_data = total_rev_food_df
else:
warning_mess = '%s:%s %s:%s %s' % (
col_name.CLIENT, self.client_id, col_name.H_ID,
self.hotel_id, 'Total_data_empty:1')
log.warning(warning_mess)