DEPR: pandas.stats.var, pandas.stats.plm, pandas.stats.ols, pandas.stats.fama_macbeth

doc/source/whatsnew/v0.18.0.txt

@@ -253,6 +253,8 @@ Deprecations
   For example, instead of ``s.rolling(window=5,freq='D').max()`` to get the max value on a rolling 5 Day window, one could use ``s.resample('D',how='max').rolling(window=5).max()``, which first resamples the data to daily data, then provides a rolling 5 day window.
 
 - ``pd.tseries.frequencies.get_offset_name`` function is deprecated. Use offset's ``.freqstr`` property as alternative (:issue:`11192`)
+- ``pandas.stats.fama_macbeth`` routines are deprecated and will be removed in a future version (:issue:`6077`)
+- ``pandas.stats.ols``, ``pandas.stats.plm`` and ``pandas.stats.var`` routines are deprecated and will be removed in a future version (:issue:`6077`)
 
 .. _whatsnew_0180.prior_deprecations:
 
@@ -346,4 +348,4 @@ Bug Fixes
 
 - Bug in ``read_sql`` with pymysql connections failing to return chunked data (:issue:`11522`)
 
-- Bug in ``DataFrame`` when masking an empty ``DataFrame`` (:issue:`11859`)
+- Bug in ``DataFrame`` when masking an empty ``DataFrame`` (:issue:`11859`)

pandas/stats/fama_macbeth.py

@@ -17,7 +17,7 @@ def fama_macbeth(**kwargs):
 
     nw_lags_beta: int
        Newey-West adjusts the betas by the given lags
-    """
+       """
     window_type = kwargs.get('window_type')
     if window_type is None:
         klass = FamaMacBeth
@@ -32,6 +32,12 @@ def __init__(self, y, x, intercept=True, nw_lags=None,
                  nw_lags_beta=None,
                  entity_effects=False, time_effects=False, x_effects=None,
                  cluster=None, dropped_dummies=None, verbose=False):
+        import warnings
+        warnings.warn("The pandas.stats.fama_macbeth module is deprecated and will be "
+                      "removed in a future version. We refer to external packages "
+                      "like statsmodels, see here: http://statsmodels.sourceforge.net/stable/index.html",
+                      FutureWarning, stacklevel=4)
+
         if dropped_dummies is None:
                 dropped_dummies = {}
         self._nw_lags_beta = nw_lags_beta

pandas/stats/ols.py

@@ -47,6 +47,12 @@ class OLS(StringMixin):
 
     def __init__(self, y, x, intercept=True, weights=None, nw_lags=None,
                  nw_overlap=False):
+        import warnings
+        warnings.warn("The pandas.stats.ols module is deprecated and will be "
+                      "removed in a future version. We refer to external packages "
+                      "like statsmodels, see some examples here: http://statsmodels.sourceforge.net/stable/regression.html",
+                      FutureWarning, stacklevel=4)
+
         try:
             import statsmodels.api as sm
         except ImportError:
@@ -1197,8 +1203,11 @@ def _results(self):
 
     @cache_readonly
     def _window_time_obs(self):
-        window_obs = moments.rolling_sum(self._time_obs_count > 0,
-                                         self._window, min_periods=1)
+        window_obs = (Series(self._time_obs_count > 0)
+                      .rolling(self._window, min_periods=1)
+                      .sum()
+                      .values
+                      )
 
         window_obs[np.isnan(window_obs)] = 0
         return window_obs.astype(int)
@@ -1211,8 +1220,7 @@ def _nobs_raw(self):
             # expanding case
             window = len(self._index)
 
-        result = moments.rolling_sum(self._time_obs_count, window,
-                                     min_periods=1)
+        result = Series(self._time_obs_count).rolling(window, min_periods=1).sum().values
 
         return result.astype(int)
 

pandas/stats/plm.py

@@ -34,6 +34,11 @@ def __init__(self, y, x, weights=None, intercept=True, nw_lags=None,
                  entity_effects=False, time_effects=False, x_effects=None,
                  cluster=None, dropped_dummies=None, verbose=False,
                  nw_overlap=False):
+        import warnings
+        warnings.warn("The pandas.stats.plm module is deprecated and will be "
+                      "removed in a future version. We refer to external packages "
+                      "like statsmodels, see some examples here: http://statsmodels.sourceforge.net/stable/mixed_linear.html",
+                      FutureWarning, stacklevel=4)
         self._x_orig = x
         self._y_orig = y
         self._weights = weights
@@ -732,6 +737,12 @@ def __init__(self, y, x, window_type='full_sample', window=None,
                  min_periods=None, intercept=True, nw_lags=None,
                  nw_overlap=False):
 
+        import warnings
+        warnings.warn("The pandas.stats.plm module is deprecated and will be "
+                      "removed in a future version. We refer to external packages "
+                      "like statsmodels, see some examples here: http://statsmodels.sourceforge.net/stable/mixed_linear.html",
+                      FutureWarning, stacklevel=4)
+
         for attr in self.ATTRIBUTES:
             setattr(self.__class__, attr, create_ols_attr(attr))
 

pandas/stats/tests/test_fama_macbeth.py

@@ -4,6 +4,7 @@
 
 from pandas.compat import range
 from pandas import compat
+import pandas.util.testing as tm
 import numpy as np
 
 
@@ -23,8 +24,9 @@ def testFamaMacBethRolling(self):
     def checkFamaMacBethExtended(self, window_type, x, y, **kwds):
         window = 25
 
-        result = fama_macbeth(y=y, x=x, window_type=window_type, window=window,
-                              **kwds)
+        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+            result = fama_macbeth(y=y, x=x, window_type=window_type, window=window,
+                                  **kwds)
         self._check_stuff_works(result)
 
         index = result._index
@@ -43,10 +45,12 @@ def checkFamaMacBethExtended(self, window_type, x, y, **kwds):
                 x2[k] = v.truncate(start, end)
             y2 = y.truncate(start, end)
 
-            reference = fama_macbeth(y=y2, x=x2, **kwds)
+            with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+                reference = fama_macbeth(y=y2, x=x2, **kwds)
             assert_almost_equal(reference._stats, result._stats[:, i])
 
-        static = fama_macbeth(y=y2, x=x2, **kwds)
+        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+            static = fama_macbeth(y=y2, x=x2, **kwds)
         self._check_stuff_works(static)
 
     def _check_stuff_works(self, result):

pandas/stats/tests/test_math.py

@@ -52,7 +52,8 @@ def test_solve_rect(self):
 
         b = Series(np.random.randn(N), self.frame.index)
         result = pmath.solve(self.frame, b)
-        expected = ols(y=b, x=self.frame, intercept=False).beta
+        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+            expected = ols(y=b, x=self.frame, intercept=False).beta
         self.assertTrue(np.allclose(result, expected))
 
     def test_inv_illformed(self):