CLN: fix flake8 warnings in pandas/stats

Author: wesm

pandas/stats/api.py

@@ -4,6 +4,8 @@
 
 # pylint: disable-msg=W0611,W0614,W0401
 
+# flake8: noqa
+
 from pandas.stats.moments import *
 from pandas.stats.interface import ols
 from pandas.stats.fama_macbeth import fama_macbeth

pandas/stats/common.py

@@ -5,9 +5,10 @@
     2: 'expanding'
 }
 # also allow 'rolling' as key
-_WINDOW_TYPES.update((v, v) for k,v in list(_WINDOW_TYPES.items()))
+_WINDOW_TYPES.update((v, v) for k, v in list(_WINDOW_TYPES.items()))
 _ADDITIONAL_CLUSTER_TYPES = set(("entity", "time"))
 
+
 def _get_cluster_type(cluster_type):
     # this was previous behavior
     if cluster_type is None:
@@ -20,15 +21,18 @@ def _get_cluster_type(cluster_type):
             return final_type
         raise ValueError('Unrecognized cluster type: %s' % cluster_type)
 
+
 def _get_window_type(window_type):
     # e.g., 0, 1, 2
     final_type = _WINDOW_TYPES.get(window_type)
     # e.g., 'full_sample'
-    final_type = final_type or _WINDOW_TYPES.get(str(window_type).lower().replace(" ", "_"))
+    final_type = final_type or _WINDOW_TYPES.get(
+        str(window_type).lower().replace(" ", "_"))
     if final_type is None:
         raise ValueError('Unrecognized window type: %s' % window_type)
     return final_type
 
+
 def banner(text, width=80):
     """
 

pandas/stats/fama_macbeth.py

@@ -7,6 +7,7 @@
 import pandas.stats.common as common
 from pandas.util.decorators import cache_readonly
 
+# flake8: noqa
 
 def fama_macbeth(**kwargs):
     """Runs Fama-MacBeth regression.
@@ -28,6 +29,7 @@ def fama_macbeth(**kwargs):
 
 
 class FamaMacBeth(StringMixin):
+
     def __init__(self, y, x, intercept=True, nw_lags=None,
                  nw_lags_beta=None,
                  entity_effects=False, time_effects=False, x_effects=None,
@@ -39,7 +41,7 @@ def __init__(self, y, x, intercept=True, nw_lags=None,
                       FutureWarning, stacklevel=4)
 
         if dropped_dummies is None:
-                dropped_dummies = {}
+            dropped_dummies = {}
         self._nw_lags_beta = nw_lags_beta
 
         from pandas.stats.plm import MovingPanelOLS
@@ -99,7 +101,7 @@ def _results(self):
     def _coef_table(self):
         buffer = StringIO()
         buffer.write('%13s %13s %13s %13s %13s %13s\n' %
-                    ('Variable', 'Beta', 'Std Err', 't-stat', 'CI 2.5%', 'CI 97.5%'))
+                     ('Variable', 'Beta', 'Std Err', 't-stat', 'CI 2.5%', 'CI 97.5%'))
         template = '%13s %13.4f %13.4f %13.2f %13.4f %13.4f\n'
 
         for i, name in enumerate(self._cols):
@@ -148,12 +150,13 @@ def summary(self):
 
 
 class MovingFamaMacBeth(FamaMacBeth):
+
     def __init__(self, y, x, window_type='rolling', window=10,
                  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):
         if dropped_dummies is None:
-                dropped_dummies = {}
+            dropped_dummies = {}
         self._window_type = common._get_window_type(window_type)
         self._window = window
 

pandas/stats/interface.py

@@ -76,7 +76,8 @@ def ols(**kwargs):
     result = ols(y=y, x=x)
 
     # Run expanding panel OLS with window 10 and entity clustering.
-    result = ols(y=y, x=x, cluster='entity', window_type='expanding', window=10)
+    result = ols(y=y, x=x, cluster='entity', window_type='expanding',
+                 window=10)
 
     Returns
     -------
@@ -85,12 +86,11 @@ def ols(**kwargs):
     """
 
     if (kwargs.get('cluster') is not None and
-        kwargs.get('nw_lags') is not None):
+            kwargs.get('nw_lags') is not None):
         raise ValueError(
             'Pandas OLS does not work with Newey-West correction '
             'and clustering.')
 
-
     pool = kwargs.get('pool')
     if 'pool' in kwargs:
         del kwargs['pool']

pandas/stats/misc.py

@@ -2,9 +2,10 @@
 from pandas import compat
 import numpy as np
 
-from pandas.core.api import Series, DataFrame, isnull, notnull
+from pandas.core.api import Series, DataFrame
 from pandas.core.series import remove_na
-from pandas.compat import zip
+from pandas.compat import zip, lrange
+import pandas.core.common as com
 
 
 def zscore(series):
@@ -42,6 +43,7 @@ def correl_ts(frame1, frame2):
 def correl_xs(frame1, frame2):
     return correl_ts(frame1.T, frame2.T)
 
+
 def percentileofscore(a, score, kind='rank'):
     """The percentile rank of a score relative to a list of scores.
 
@@ -131,6 +133,7 @@ def percentileofscore(a, score, kind='rank'):
     else:
         raise ValueError("kind can only be 'rank', 'strict', 'weak' or 'mean'")
 
+
 def percentileRank(frame, column=None, kind='mean'):
     """
     Return score at percentile for each point in time (cross-section)