fixes

Author: jreback

pandas/index.pyx

@@ -556,7 +556,8 @@ cdef inline bint _is_utc(object tz):
 cdef class MultiIndexEngine(IndexEngine):
 
  def _call_monotonic(self, object mi):
- return mi.is_lexsorted(), mi.is_monotonic, mi.is_unique
+ # defer these back to the mi iteself
+ return mi.is_monotonic_increasing, mi.is_monotonic_decreasing, mi.is_unique
 
  def get_backfill_indexer(self, other, limit=None):
  # we coerce to ndarray-of-tuples

pandas/indexes/multi.py

@@ -666,6 +666,18 @@ def _has_complex_internals(self):
 
  @cache_readonly
  def is_monotonic(self):
+ """
+ return if the index is monotonic increasing (only equal or
+ increasing) values.
+ """
+ return self.is_monotonic_increasing
+
+ @cache_readonly
+ def is_monotonic_increasing(self):
+ """
+ return if the index is monotonic increasing (only equal or
+ increasing) values.
+ """
 
  # reversed() because lexsort() wants the most significant key last.
  values = [self._get_level_values(i)
@@ -678,6 +690,14 @@ def is_monotonic(self):
  # we have mixed types and np.lexsort is not happy
  return Index(self.values).is_monotonic
 
+ @property
+ def is_monotonic_decreasing(self):
+ """
+ return if the index is monotonic decreasing (only equal or
+ decreasing) values.
+ """
+ return False
+
  @cache_readonly
  def is_unique(self):
  return not self.duplicated().any()
@@ -1921,17 +1941,8 @@ def partial_selection(key, indexer=None):
  return partial_selection(key, indexer)
 
  key = tuple(self[indexer].tolist()[0])
-
- try:
  return (self._engine.get_loc(
  _values_from_object(key)), None)
- except ValueError:
- # if we hae a very odd MultiIndex,
- # e.g. with embedded tuples, this might fail
- # TODO: should prob not allow construction of a MI
- # like this in the first place
- return Index(self.values).get_loc(key)
-
  else:
  return partial_selection(key)
  else:

pandas/src/hashtable_class_helper.pxi.in

@@ -881,7 +881,11 @@ cdef class MultiIndexHashTable(HashTable):
  khiter_t k
  uint64_t value
 
- value = self.mi._hashed_indexing_key(key)
+ try:
+ value = self.mi._hashed_indexing_key(key)
+ except TypeError:
+ return False
+
  k = kh_get_uint64(self.table, value)
  if k != self.table.n_buckets:
  loc = self.table.vals[k]

pandas/tests/frame/test_mutate_columns.py

@@ -1,11 +1,11 @@
 # -*- coding: utf-8 -*-
 
 from __future__ import print_function
-
+import pytest
 from pandas.compat import range, lrange
 import numpy as np
 
-from pandas import DataFrame, Series, Index
+from pandas import DataFrame, Series, Index, MultiIndex
 
 from pandas.util.testing import (assert_series_equal,
  assert_frame_equal,
@@ -165,6 +165,23 @@ def test_delitem(self):
  del self.frame['A']
  self.assertNotIn('A', self.frame)
 
+ def test_delitem_multiindex(self):
+ midx = MultiIndex.from_product([['A', 'B'], [1, 2]])
+ df = DataFrame(np.random.randn(4, 4), columns=midx)
+ assert len(df.columns) == 4
+
+ result = df['A']
+ assert isinstance(result, DataFrame)
+ del df['A']
+
+ assert len(df.columns) == 2
+
+ with pytest.raises(KeyError):
+ del df[('A',)]
+
+ with pytest.raises(KeyError):
+ del df['A']
+
  def test_pop(self):
  self.frame.columns.name = 'baz'
 

pandas/tests/indexes/test_multi.py

@@ -1046,6 +1046,11 @@ def test_contains(self):
  self.assertNotIn(('bar', 'two'), self.index)
  self.assertNotIn(None, self.index)
 
+ def test_contains_top_level(self):
+ midx = MultiIndex.from_product([['A', 'B'], [1, 2]])
+ self.assertTrue('A' in midx)
+ self.assertFalse('A' in midx._engine)
+
  def test_contains_with_nat(self):
  # MI with a NaT
  mi = MultiIndex(levels=[['C'],