Merge pull request #6646 from dsm054/fix_indentation_errors

CLN: Fix many indentation errors found in #6643.

Author: jreback

doc/make.py

@@ -77,10 +77,10 @@ def upload_prev(ver, doc_root='./'):
         raise SystemExit('Upload PDF to %s from %s failed' % (ver, doc_root))
 
 def build_pandas():
-        os.chdir('..')
-        os.system('python setup.py clean')
-        os.system('python setup.py build_ext --inplace')
-        os.chdir('doc')
+    os.chdir('..')
+    os.system('python setup.py clean')
+    os.system('python setup.py build_ext --inplace')
+    os.chdir('doc')
 
 def build_prev(ver):
     if os.system('git checkout v%s' % ver) != 1:

pandas/computation/tests/test_eval.py

@@ -819,7 +819,7 @@ def testit(r_idx_type, c_idx_type, index_name):
         with warnings.catch_warnings(record=True):
             warnings.simplefilter('always', RuntimeWarning)
             for r_idx_type, c_idx_type, index_name in args:
-                    testit(r_idx_type, c_idx_type, index_name)
+                testit(r_idx_type, c_idx_type, index_name)
 
     def test_basic_frame_series_alignment(self):
         for engine, parser in ENGINES_PARSERS:

pandas/core/format.py

@@ -539,18 +539,18 @@ def write(buf, frame, column_format, strcols, longtable=False):
                         buf.write('\\bottomrule\n')
                         buf.write('\\endlastfoot\n')
                 if self.escape:
-                  crow = [(x.replace('\\', '\\textbackslash') # escape backslashes first
-                           .replace('_', '\\_')
-                           .replace('%', '\\%')
-                           .replace('$', '\\$')
-                           .replace('#', '\\#')
-                           .replace('{', '\\{')
-                           .replace('}', '\\}')
-                           .replace('~', '\\textasciitilde')
-                           .replace('^', '\\textasciicircum')
-                           .replace('&', '\\&') if x else '{}') for x in row]
+                    crow = [(x.replace('\\', '\\textbackslash') # escape backslashes first
+                             .replace('_', '\\_')
+                             .replace('%', '\\%')
+                             .replace('$', '\\$')
+                             .replace('#', '\\#')
+                             .replace('{', '\\{')
+                             .replace('}', '\\}')
+                             .replace('~', '\\textasciitilde')
+                             .replace('^', '\\textasciicircum')
+                             .replace('&', '\\&') if x else '{}') for x in row]
                 else:
-                  crow = [x if x else '{}' for x in row]
+                    crow = [x if x else '{}' for x in row]
                 buf.write(' & '.join(crow))
                 buf.write(' \\\\\n')
 
@@ -2104,7 +2104,7 @@ def detect_console_encoding():
 
     # when all else fails. this will usually be "ascii"
     if not encoding or 'ascii' in encoding.lower():
-            encoding = sys.getdefaultencoding()
+        encoding = sys.getdefaultencoding()
 
     # GH3360, save the reported defencoding at import time
     # MPL backends may change it. Make available for debugging.

pandas/core/generic.py

@@ -3598,10 +3598,10 @@ def pretty_name(x):
                 return '%.1f%%' % x
 
         def describe_numeric_1d(series, percentiles):
-                return ([series.count(), series.mean(), series.std(),
-                         series.min()] +
-                        [series.quantile(x) for x in percentiles] +
-                        [series.max()])
+            return ([series.count(), series.mean(), series.std(),
+                     series.min()] +
+                    [series.quantile(x) for x in percentiles] +
+                    [series.max()])
 
         def describe_categorical_1d(data):
             names = ['count', 'unique']

pandas/core/groupby.py

@@ -2218,9 +2218,9 @@ def transform(self, func, *args, **kwargs):
 
             # may need to astype
             try:
-               common_type = np.common_type(np.array(res), result)
-               if common_type != result.dtype:
-                   result = result.astype(common_type)
+                common_type = np.common_type(np.array(res), result)
+                if common_type != result.dtype:
+                    result = result.astype(common_type)
             except:
                 pass
 

pandas/core/indexing.py

@@ -1131,13 +1131,13 @@ def _getitem_axis(self, key, axis=0, validate_iterable=False):
         raise NotImplementedError()
 
     def _getbool_axis(self, key, axis=0):
-            labels = self.obj._get_axis(axis)
-            key = _check_bool_indexer(labels, key)
-            inds, = key.nonzero()
-            try:
-                return self.obj.take(inds, axis=axis, convert=False)
-            except Exception as detail:
-                raise self._exception(detail)
+        labels = self.obj._get_axis(axis)
+        key = _check_bool_indexer(labels, key)
+        inds, = key.nonzero()
+        try:
+            return self.obj.take(inds, axis=axis, convert=False)
+        except Exception as detail:
+            raise self._exception(detail)
 
     def _get_slice_axis(self, slice_obj, axis=0):
         """ this is pretty simple as we just have to deal with labels """
@@ -1193,7 +1193,7 @@ def _has_valid_type(self, key, axis):
                         )
 
         elif com._is_bool_indexer(key):
-                return True
+            return True
 
         elif _is_list_like(key):
 

pandas/core/internals.py

@@ -824,7 +824,7 @@ def eval(self, func, other, raise_on_error=True, try_cast=False):
         is_transposed = False
         if hasattr(other, 'ndim') and hasattr(values, 'ndim'):
             if values.ndim != other.ndim:
-                    is_transposed = True
+                is_transposed = True
             else:
                 if values.shape == other.shape[::-1]:
                     is_transposed = True
@@ -2981,7 +2981,7 @@ def _is_indexed_like(self, other):
     def equals(self, other):
         self_axes, other_axes = self.axes, other.axes
         if len(self_axes) != len(other_axes):
-           return False
+            return False
         if not all (ax1.equals(ax2) for ax1, ax2 in zip(self_axes, other_axes)):
             return False
         self._consolidate_inplace()

pandas/core/series.py

@@ -672,7 +672,7 @@ def _set_with(self, key, value):
                 else:
                     return self._set_values(key, value)
             elif key_type == 'boolean':
-                    self._set_values(key.astype(np.bool_), value)
+                self._set_values(key.astype(np.bool_), value)
             else:
                 self._set_labels(key, value)
 

pandas/io/excel.py

@@ -291,10 +291,10 @@ def _parse_excel(self, sheetname=0, header=0, skiprows=None, skip_footer=0,
                             year = (value.timetuple())[0:3]
                             if ((not epoch1904 and year == (1899, 12, 31))
                                     or (epoch1904 and year == (1904, 1, 1))):
-                                    value = datetime.time(value.hour,
-                                                          value.minute,
-                                                          value.second,
-                                                          value.microsecond)
+                                value = datetime.time(value.hour,
+                                                      value.minute,
+                                                      value.second,
+                                                      value.microsecond)
                         else:
                             # Use the xlrd <= 0.9.2 date handling.
                             dt = xldate.xldate_as_tuple(value, epoch1904)

pandas/tests/test_common.py

@@ -75,7 +75,7 @@ def test_isnull():
     # series
     for s in [tm.makeFloatSeries(),tm.makeStringSeries(),
               tm.makeObjectSeries(),tm.makeTimeSeries(),tm.makePeriodSeries()]:
-            assert(isinstance(isnull(s), Series))
+        assert(isinstance(isnull(s), Series))
 
     # frame
     for df in [tm.makeTimeDataFrame(),tm.makePeriodFrame(),tm.makeMixedDataFrame()]: