def getMixedTypeDict():
index = Index(['a', 'b', 'c', 'd', 'e'])
data = {
'A' : [0., 1., 2., 3., 4.],
'B' : [0., 1., 0., 1., 0.],
'C' : ['foo1', 'foo2', 'foo3', 'foo4', 'foo5'],
'D' : DateRange('1/1/2009', periods=5)
}
return index, data
def setUp(self):
arr = randn(N)
arr[self._nan_locs] = np.NaN
self.arr = arr
self.rng = DateRange(datetime(2009, 1, 1), periods=N)
self.series = Series(arr.copy(), index=self.rng)
self.frame = DataFrame(randn(N, K),
index=self.rng,
columns=np.arange(K))
def setUp(self):
date_index = DateRange(datetime(2009, 12, 11), periods=3, offset=bday)
ts = Series([3, 1, 4], index=date_index)
self.TS1 = ts
date_index = DateRange(datetime(2009, 12, 11), periods=5, offset=bday)
ts = Series([1, 5, 9, 2, 6], index=date_index)
self.TS2 = ts
date_index = DateRange(datetime(2009, 12, 11), periods=3, offset=bday)
ts = Series([5, NaN, 3], index=date_index)
self.TS3 = ts
date_index = DateRange(datetime(2009, 12, 11), periods=5, offset=bday)
ts = Series([NaN, 5, 8, 9, 7], index=date_index)
self.TS4 = ts
data = {'x1': self.TS2, 'x2': self.TS4}
self.DF1 = DataFrame(data=data)
data = {'x1': self.TS2, 'x2': self.TS4}
self.DICT1 = data
def makeDateIndex(k):
dates = list(DateRange(datetime(2000, 1, 1), periods=k))
return Index(dates)
from datetime import datetime
import string
import numpy as np
from pandas.core.api import Series, DataFrame, DateRange
from pandas.stats.api import ols
N = 100
start = datetime(2009, 9, 2)
dateRange = DateRange(start, periods=N)
def makeDataFrame():
data = DataFrame(np.random.randn(N, 7),
columns=list(string.ascii_uppercase[:7]),
index=dateRange)
return data
def makeSeries():
return Series(np.random.randn(N), index=dateRange)
#-------------------------------------------------------------------------------
# Standard rolling linear regression
X = makeDataFrame()
Y = makeSeries()
# pylint: disable-msg=W0611,W0402
from datetime import datetime
import string
import unittest
import nose
import numpy as np
from pandas.core.api import DataFrame, DateRange
from pandas.util.testing import assert_almost_equal # imported in other tests
N = 100
K = 4
start = datetime(2007, 1, 1)
DATE_RANGE = DateRange(start, periods=N)
COLS = ['Col' + c for c in string.ascii_uppercase[:K]]
def makeDataFrame():
data = DataFrame(np.random.randn(N, K), columns=COLS, index=DATE_RANGE)
return data
def getBasicDatasets():
A = makeDataFrame()
B = makeDataFrame()
C = makeDataFrame()