def _infer_freq(dates):
try:
from pandas.tseries.api import infer_freq
freq = infer_freq(dates)
return freq
except ImportError:
pass
timedelta = datetime.timedelta
nobs = min(len(dates), 6)
if nobs == 1:
raise ValueError("Cannot infer frequency from one date")
if hasattr(dates, 'values'):
dates = dates.values # can't do a diff on a DateIndex
diff = np.diff(dates[:nobs])
delta = _add_datetimes(diff)
nobs -= 1 # after diff
if delta == timedelta(nobs): #greedily assume 'D'
return 'D'
elif delta == timedelta(nobs + 2):
return 'B'
elif delta == timedelta(7*nobs):
return 'W'
elif delta >= timedelta(28*nobs) and delta <= timedelta(31*nobs):
return 'M'
elif delta >= timedelta(90*nobs) and delta <= timedelta(92*nobs):
return 'Q'
elif delta >= timedelta(365 * nobs) and delta <= timedelta(366 * nobs):
return 'A'
else:
return
def _infer_freq(dates):
try:
from pandas.tseries.api import infer_freq
freq = infer_freq(dates)
return _pandas_mapping.get(freq, freq)
except ImportError:
pass
timedelta = datetime.timedelta
nobs = min(len(dates), 6)
if nobs == 1:
raise ValueError("Cannot infer frequency from one date")
diff = np.diff(dates[:nobs])
delta = _add_datetimes(diff)
nobs -= 1 # after diff
if delta == timedelta(nobs): #greedily assume 'D'
return 'D'
elif delta == timedelta(nobs + 2):
return 'B'
elif delta == timedelta(7*nobs):
return 'W'
elif delta >= timedelta(28*nobs) and delta <= timedelta(31*nobs):
return 'M'
elif delta >= timedelta(90*nobs) and delta <= timedelta(92*nobs):
return 'Q'
elif delta >= timedelta(365 * nobs) and delta <= timedelta(366 * nobs):
return 'A'
else:
return
def _infer_freq(dates):
maybe_freqstr = getattr(dates, 'freqstr', None)
if maybe_freqstr is not None:
return maybe_freqstr
# might be a DatetimeIndex
elif hasattr(dates, "inferred_freq"): # see pandas/6637 and others
return dates.inferred_freq
# try to infer from a regular index or something
from pandas.tseries.api import infer_freq
freq = infer_freq(dates)
return freq
def _infer_freq(dates):
maybe_freqstr = getattr(dates, 'freqstr', None)
if maybe_freqstr is not None:
return maybe_freqstr
# might be a DatetimeIndex
elif hasattr(dates, "inferred_freq"): # see pandas/6637 and others
return dates.inferred_freq
# try to infer from a regular index or something
from pandas.tseries.api import infer_freq
freq = infer_freq(dates)
return freq
def pandas_to_series_spec(x):
# from statsmodels.tools.data import _check_period_index
# check_period_index(x)
if hasattr(x, 'columns'): # convert to series
if len(x.columns) > 1:
raise ValueError("Does not handle DataFrame with more than one "
"column")
x = x[x.columns[0]]
data = "({0})".format("\n".join(map(str, x.values.tolist())))
# get periodicity
# get start / first data
# give it a title
try:
period = _freq_to_period[x.index.freqstr]
except (AttributeError, ValueError):
from pandas.tseries.api import infer_freq
period = _freq_to_period[infer_freq(x.index)]
start_date = x.index[0]
if period == 12:
year, stperiod = start_date.year, start_date.month
elif period == 4:
year, stperiod = start_date.year, start_date.quarter
else: # pragma: no cover
raise ValueError("Only monthly and quarterly periods are supported."
" Please report or send a pull request if you want "
"this extended.")
if hasattr(x, 'name'):
name = x.name or "Unnamed Series"
else:
name = 'Unnamed Series'
series_spec = SeriesSpec(data=data,
name=name,
period=period,
title=name,
start="{0}.{1}".format(year, stperiod))
return series_spec
def pandas_to_series_spec(x):
# from statsmodels.tools.data import _check_period_index
# check_period_index(x)
if hasattr(x, 'columns'): # convert to series
if len(x.columns) > 1:
raise ValueError("Does not handle DataFrame with more than one "
"column")
x = x[x.columns[0]]
data = "({0})".format("\n".join(map(str, x.values.tolist())))
# get periodicity
# get start / first data
# give it a title
try:
period = _freq_to_period[x.index.freqstr]
except (AttributeError, ValueError):
from pandas.tseries.api import infer_freq
period = _freq_to_period[infer_freq(x.index)]
start_date = x.index[0]
if period == 12:
year, stperiod = start_date.year, start_date.month
elif period == 4:
year, stperiod = start_date.year, start_date.quarter
else: # pragma: no cover
raise ValueError("Only monthly and quarterly periods are supported."
" Please report or send a pull request if you want "
"this extended.")
if hasattr(x, 'name'):
name = x.name or "Unnamed Series"
else:
name = 'Unnamed Series'
series_spec = SeriesSpec(data=data, name=name, period=period,
title=name, start="{0}.{1}".format(year,
stperiod))
return series_spec
