def get_daily_data(cls, root_path, company_name, unit, year_value,
month_value, date_value):
data_frame = DataFrameFunction.get_data_frame_from_merged_pkl(
root_path, company_name)
target_date = datetime(int(year_value), int(month_value),
int(date_value))
data_frame = data_frame[(data_frame['date'] == target_date)]
result = None
if unit == '1H':
result = data_frame.to_json(date_format='iso').replace(
'T', ' ').replace(':00.000Z', '')
return json.loads(result)
def get(cls, root_path, company_name, unit, from_value, to_value):
data_frame = DataFrameFunction.get_data_frame_from_merged_pkl(
root_path, company_name)
from_values = from_value.split('/')
to_values = to_value.split('/')
from_date = datetime(int(from_values[0]), int(from_values[1]), 1)
to_date = datetime(int(to_values[0]), int(to_values[1]),
1) + relativedelta(months=1, days=-1)
data_frame = data_frame[(from_date <= data_frame['date'])
& (data_frame['date'] <= to_date)]
result = None
if unit == 'y':
result = cls.sum_group_by_year(data_frame)
elif unit == 'ym':
result = cls.sum_group_by_year_and_month(data_frame)
elif unit == 'ymd':
result = cls.sum_group_by_year_and_month_and_date(data_frame)
return json.loads(result)
def count(cls, root_path, company_name):
data_frame = DataFrameFunction.get_data_frame_from_merged_pkl(
root_path, company_name)
return len(data_frame.index)