From edba48974460af52fbc96943a9d1d306e7b72018 Mon Sep 17 00:00:00 2001
From: jreback <jeff@reback.net>
Date: Thu, 13 Feb 2014 18:00:08 -0500
Subject: [PATCH] BUG: Bug in setting complex dtypes via boolean indexing
 (GH6345)

---
 doc/source/release.rst     | 1 +
 pandas/core/internals.py   | 6 +++++-
 pandas/tests/test_frame.py | 7 +++++++
 3 files changed, 13 insertions(+), 1 deletion(-)

diff --git a/doc/source/release.rst b/doc/source/release.rst
index 829a21f8033ca..78678a0ee81a6 100644
--- a/doc/source/release.rst
+++ b/doc/source/release.rst
@@ -96,6 +96,7 @@ Bug Fixes
 - Bug in ``DataFrame.replace()`` when passing a non- ``bool``
   ``to_replace`` argument (:issue:`6332`)
 - Raise when trying to align on different levels of a multi-index assignment (:issue:`3738`)
+- Bug in setting complex dtypes via boolean indexing (:issue:`6345`)
 
 pandas 0.13.1
 -------------
diff --git a/pandas/core/internals.py b/pandas/core/internals.py
index faf8587460825..2fd579e5d2059 100644
--- a/pandas/core/internals.py
+++ b/pandas/core/internals.py
@@ -1221,7 +1221,11 @@ class ComplexBlock(FloatOrComplexBlock):
     is_complex = True
 
     def _can_hold_element(self, element):
-        return isinstance(element, complex)
+        if is_list_like(element):
+            element = np.array(element)
+            return issubclass(element.dtype.type, (np.floating, np.integer, np.complexfloating))
+        return (isinstance(element, (float, int, complex, np.float_, np.int_)) and
+                not isinstance(bool, np.bool_))
 
     def _try_cast(self, element):
         try:
diff --git a/pandas/tests/test_frame.py b/pandas/tests/test_frame.py
index e73f1e792e826..da60326fc232f 100644
--- a/pandas/tests/test_frame.py
+++ b/pandas/tests/test_frame.py
@@ -8736,6 +8736,13 @@ def create():
         result = df.where(pd.notnull(df),DataFrame(1,index=df.index,columns=df.columns))
         assert_frame_equal(result, expected)
 
+    def test_where_complex(self):
+        # GH 6345
+        expected = DataFrame([[1+1j, 2], [np.nan, 4+1j]], columns=['a', 'b'])
+        df = DataFrame([[1+1j, 2], [5+1j, 4+1j]], columns=['a', 'b'])
+        df[df.abs() >= 5] = np.nan
+        assert_frame_equal(df,expected)
+
     def test_mask(self):
         df = DataFrame(np.random.randn(5, 3))
         cond = df > 0