本文整理汇总了Python中statsmodels.base.data.handle_data函数的典型用法代码示例。如果您正苦于以下问题：Python handle_data函数的具体用法？Python handle_data怎么用？Python handle_data使用的例子？那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。
在下文中一共展示了handle_data函数的15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: setupClass
def setupClass(cls):
cls.endog = endog = pandas.DataFrame(np.random.random((10,4)),
columns=['y_1', 'y_2', 'y_3', 'y_4'])
exog = pandas.DataFrame(np.random.random((10,2)),
columns=['x_1','x_2'])
exog.insert(0, 'const', 1)
cls.exog = exog
cls.data = sm_data.handle_data(cls.endog, cls.exog)
nrows = 10
nvars = 3
neqs = 4
cls.col_input = np.random.random(nvars)
cls.col_result = pandas.Series(cls.col_input,
index=exog.columns)
cls.row_input = np.random.random(nrows)
cls.row_result = pandas.Series(cls.row_input,
index=exog.index)
cls.cov_input = np.random.random((nvars, nvars))
cls.cov_result = pandas.DataFrame(cls.cov_input,
index = exog.columns,
columns = exog.columns)
cls.cov_eq_input = np.random.random((neqs, neqs))
cls.cov_eq_result = pandas.DataFrame(cls.cov_eq_input,
index=endog.columns,
columns=endog.columns)
cls.col_eq_input = np.random.random((nvars, neqs))
cls.col_eq_result = pandas.DataFrame(cls.col_eq_input,
index=exog.columns,
columns=endog.columns)
cls.xnames = ['const', 'x_1', 'x_2']
cls.ynames = ['y_1', 'y_2', 'y_3', 'y_4']
cls.row_labels = cls.exog.index示例2: test_extra_kwargs_2d
def test_extra_kwargs_2d(self):
sigma = np.random.random((25, 25))
sigma = sigma + sigma.T - np.diag(np.diag(sigma))
data = sm_data.handle_data(self.y, self.X, 'drop', sigma=sigma)
idx = ~np.isnan(np.c_[self.y, self.X]).any(axis=1)
sigma = sigma[idx][:,idx]
np.testing.assert_array_equal(data.sigma, sigma)示例3: setupClass
def setupClass(cls):
super(TestStructarrays, cls).setupClass()
cls.endog = np.random.random(9).view([("y_1", "f8")]).view(np.recarray)
exog = np.random.random(9 * 3).view([("const", "f8"), ("x_1", "f8"), ("x_2", "f8")]).view(np.recarray)
exog["const"] = 1
cls.exog = exog
cls.data = sm_data.handle_data(cls.endog, cls.exog)
cls.xnames = ["const", "x_1", "x_2"]
cls.ynames = "y_1"示例4: test_drop
def test_drop(self):
y = self.y
X = self.X
combined = np.c_[y, X]
idx = ~np.isnan(combined).any(axis=1)
y = y[idx]
X = X[idx]
data = sm_data.handle_data(self.y, self.X, 'drop')
np.testing.assert_array_equal(data.endog, y)
np.testing.assert_array_equal(data.exog, X)示例5: setup_class
def setup_class(cls):
cls.endog = pandas.DataFrame(np.random.random(10), columns=['y_1'])
mi = pandas.MultiIndex.from_product([['x'], ['1', '2']])
exog = pandas.DataFrame(np.random.random((10, 2)), columns=mi)
exog_flattened_idx = pandas.Index(['const', 'x_1', 'x_2'])
exog.insert(0, 'const', 1)
cls.exog = exog
cls.data = sm_data.handle_data(cls.endog, cls.exog)
nrows = 10
nvars = 3
cls.col_input = np.random.random(nvars)
cls.col_result = pandas.Series(cls.col_input, index=exog_flattened_idx)
cls.row_input = np.random.random(nrows)
cls.row_result = pandas.Series(cls.row_input, index=exog.index)
cls.cov_input = np.random.random((nvars, nvars))
cls.cov_result = pandas.DataFrame(cls.cov_input,
index=exog_flattened_idx,
columns=exog_flattened_idx)
cls.xnames = ['const', 'x_1', 'x_2']
cls.ynames = 'y_1'
cls.row_labels = cls.exog.index示例6: setup_class
def setup_class(cls):
cls.endog = np.random.random(10).tolist()
exog = pandas.DataFrame(np.random.random((10,2)),
columns=['x_1','x_2'])
exog.insert(0, 'const', 1)
cls.exog = exog
cls.data = sm_data.handle_data(cls.endog, cls.exog)
nrows = 10
nvars = 3
cls.col_input = np.random.random(nvars)
cls.col_result = pandas.Series(cls.col_input,
index=exog.columns)
cls.row_input = np.random.random(nrows)
cls.row_result = pandas.Series(cls.row_input,
index=exog.index)
cls.cov_input = np.random.random((nvars, nvars))
cls.cov_result = pandas.DataFrame(cls.cov_input,
index = exog.columns,
columns = exog.columns)
cls.xnames = ['const', 'x_1', 'x_2']
cls.ynames = 'y'
cls.row_labels = cls.exog.index示例7: test_labels
def test_labels(self):
2, 10, 14
labels = pandas.Index([0, 1, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 15,
16, 17, 18, 19, 20, 21, 22, 23, 24])
data = sm_data.handle_data(self.y, self.X, 'drop')
np.testing.assert_(data.row_labels.equals(labels))示例8: test_mv_endog
def test_mv_endog(self):
y = self.X
y = y.ix[~np.isnan(y.values).any(axis=1)]
data = sm_data.handle_data(self.X, None, 'drop')
np.testing.assert_array_equal(data.endog, y.values)示例9: test_endog_only_drop
def test_endog_only_drop(self):
y = self.y
y = y.dropna()
data = sm_data.handle_data(self.y, None, 'drop')
np.testing.assert_array_equal(data.endog, y.values)示例10: test_none
def test_none(self):
data = sm_data.handle_data(self.y, self.X, 'none')
np.testing.assert_array_equal(data.endog, self.y.values)
np.testing.assert_array_equal(data.exog, self.X.values)示例11: test_raise_no_missing
def test_raise_no_missing(self):
# smoke test for #1700
sm_data.handle_data(pandas.Series(np.random.random(20)),
pandas.DataFrame(np.random.random((20, 2))),
'raise')示例12: test_extra_kwargs_1d
def test_extra_kwargs_1d(self):
weights = np.random.random(25)
data = sm_data.handle_data(self.y, self.X, 'drop', weights=weights)
idx = ~np.isnan(np.c_[self.y, self.X]).any(axis=1)
weights = weights[idx]
np.testing.assert_array_equal(data.weights, weights)示例13: test_none
def test_none(self):
data = sm_data.handle_data(self.y, self.X, 'none', hasconst=False)
np.testing.assert_array_equal(data.endog, self.y)
np.testing.assert_array_equal(data.exog, self.X)示例14: test_pandas_noconstant
def test_pandas_noconstant(self):
exog = self.data.exog.copy()
data = sm_data.handle_data(self.data.endog, exog)
np.testing.assert_equal(data.k_constant, 0)
np.testing.assert_equal(data.const_idx, None)示例15: test_array_noconstant
def test_array_noconstant(self):
exog = self.data.exog.copy()
data = sm_data.handle_data(self.data.endog.values, exog.values)
np.testing.assert_equal(data.k_constant, 0)
np.testing.assert_equal(data.const_idx, None)