def fillforward(df):
"""
Take a lower than day freq, and map it to business days.
This is to make mapping to a daily chart easy and helps handle
business days that vacations.
"""
return df.asfreq(datetools.BDay(), method='pad')
import re
import datetime
from pandas import datetools as pandas_datetools
import numpy as np
from statsmodels.compatnp.py3k import asstr
#NOTE: All of these frequencies assume end of period (except wrt time)
try:
from pandas.tseries.frequencies import get_offset
class _freq_to_pandas_class(object):
# being lazy, don't want to replace dictionary below
def __getitem__(self, key):
return get_offset(key)
_freq_to_pandas = _freq_to_pandas_class()
except ImportError, err:
_freq_to_pandas = {'B' : pandas_datetools.BDay(1),
'D' : pandas_datetools.day,
'W' : pandas_datetools.Week(weekday=6),
'M' : pandas_datetools.monthEnd,
'A' : pandas_datetools.yearEnd,
'Q' : pandas_datetools.quarterEnd}
def _index_date(date, dates):
"""
Gets the index number of a date in a date index.
Works in-sample and will return one past the end of the dates since
prediction can start one out.
Currently used to validate prediction start dates.
from pandas import datetools as pandas_datetools
import numpy as np
#NOTE: All of these frequencies assume end of period (except wrt time)
try:
from pandas.tseries.frequencies import get_offset
class _freq_to_pandas_class(object):
# being lazy, don't want to replace dictionary below
def __getitem__(self, key):
return get_offset(key)
_freq_to_pandas = _freq_to_pandas_class()
except ImportError, err:
_freq_to_pandas = {
'B': pandas_datetools.BDay(1),
'D': pandas_datetools.day,
'W': pandas_datetools.Week(weekday=6),
'M': pandas_datetools.monthEnd,
'A': pandas_datetools.yearEnd,
'Q': pandas_datetools.quarterEnd
}
def _index_date(date, dates):
"""
Gets the index number of a date in a date index.
Works in-sample and will return one past the end of the dates since
prediction can start one out.