from nose import SkipTest
from numpy.testing import assert_
from statsmodels.tsa.base.datetools import dates_from_range
from statsmodels.tsa.x13 import _find_x12, x13_arima_select_order
x13path = _find_x12()
if x13path is False:
_have_x13 = False
else:
_have_x13 = True
class TestX13(object):
@classmethod
def setupClass(cls):
if not _have_x13:
raise SkipTest("X13/X12 not available")
import pandas as pd
from statsmodels.datasets import macrodata, co2
dta = macrodata.load_pandas().data
dates = dates_from_range("1959Q1", "2009Q3")
index = pd.DatetimeIndex(dates)
dta.index = index
cls.quarterly_data = dta.dropna()
dta = co2.load_pandas().data
dta["co2"] = dta.co2.interpolate()
import pandas as pd
import pytest
from statsmodels.datasets import macrodata, co2
from statsmodels.tsa.x13 import (_find_x12, x13_arima_select_order,
x13_arima_analysis)
x13path = _find_x12()
pytestmark = pytest.mark.skipif(x13path is False,
reason='X13/X12 not available')
dta = macrodata.load_pandas().data
index = pd.period_range(start='1959Q1', end='2009Q3', freq='Q')
dta.index = index
quarterly_data = dta.dropna()
dta = co2.load_pandas().data
dta['co2'] = dta.co2.interpolate()
monthly_data = dta.resample('M')
# change in pandas 0.18 resample is deferred object
if not isinstance(monthly_data, (pd.DataFrame, pd.Series)):
monthly_data = monthly_data.mean()
monthly_start_data = dta.resample('MS')
if not isinstance(monthly_start_data, (pd.DataFrame, pd.Series)):
monthly_start_data = monthly_start_data.mean()
data = (monthly_data, monthly_start_data, monthly_data.co2,
monthly_start_data.co2, quarterly_data.realgdp,
quarterly_data[['realgdp']])