本文整理汇总了Python中pythalesians.timeseries.calcs.timeseriescalcs.TimeSeriesCalcs.average_by_month_day_by_bus_day方法的典型用法代码示例。如果您正苦于以下问题：Python TimeSeriesCalcs.average_by_month_day_by_bus_day方法的具体用法？Python TimeSeriesCalcs.average_by_month_day_by_bus_day怎么用？Python TimeSeriesCalcs.average_by_month_day_by_bus_day使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类pythalesians.timeseries.calcs.timeseriescalcs.TimeSeriesCalcs的用法示例。
在下文中一共展示了TimeSeriesCalcs.average_by_month_day_by_bus_day方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: bus_day_of_month_seasonality
# 需要导入模块: from pythalesians.timeseries.calcs.timeseriescalcs import TimeSeriesCalcs [as 别名]
# 或者: from pythalesians.timeseries.calcs.timeseriescalcs.TimeSeriesCalcs import average_by_month_day_by_bus_day [as 别名]
def bus_day_of_month_seasonality(
self,
data_frame,
month_list=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12],
cum=True,
cal="FX",
partition_by_month=True,
):
tsc = TimeSeriesCalcs()
tsf = TimeSeriesFilter()
data_frame.index = pandas.to_datetime(data_frame.index)
data_frame = tsf.filter_time_series_by_holidays(data_frame, cal)
monthly_seasonality = tsc.average_by_month_day_by_bus_day(data_frame, cal)
monthly_seasonality = monthly_seasonality.loc[month_list]
if partition_by_month:
monthly_seasonality = monthly_seasonality.unstack(level=0)
if cum is True:
monthly_seasonality.ix[0] = numpy.zeros(len(monthly_seasonality.columns))
if partition_by_month:
monthly_seasonality.index = monthly_seasonality.index + 1 # shifting index
monthly_seasonality = monthly_seasonality.sort() # sorting by index
monthly_seasonality = tsc.create_mult_index(monthly_seasonality)
return monthly_seasonality示例2: bus_day_of_month_seasonality
# 需要导入模块: from pythalesians.timeseries.calcs.timeseriescalcs import TimeSeriesCalcs [as 别名]
# 或者: from pythalesians.timeseries.calcs.timeseriescalcs.TimeSeriesCalcs import average_by_month_day_by_bus_day [as 别名]
def bus_day_of_month_seasonality(self, data_frame,
month_list = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], cum = True,
cal = "FX", partition_by_month = True, add_average = False, price_index = False):
tsc = TimeSeriesCalcs()
tsf = TimeSeriesFilter()
if price_index:
data_frame = data_frame.resample('B') # resample into business days
data_frame = tsc.calculate_returns(data_frame)
data_frame.index = pandas.to_datetime(data_frame.index)
data_frame = tsf.filter_time_series_by_holidays(data_frame, cal)
monthly_seasonality = tsc.average_by_month_day_by_bus_day(data_frame, cal)
monthly_seasonality = monthly_seasonality.loc[month_list]
if partition_by_month:
monthly_seasonality = monthly_seasonality.unstack(level=0)
if add_average:
monthly_seasonality['Avg'] = monthly_seasonality.mean(axis=1)
if cum is True:
if partition_by_month:
monthly_seasonality.loc[0] = numpy.zeros(len(monthly_seasonality.columns))
# monthly_seasonality.index = monthly_seasonality.index + 1 # shifting index
monthly_seasonality = monthly_seasonality.sort()
monthly_seasonality = tsc.create_mult_index(monthly_seasonality)
return monthly_seasonality