<h4 dir="auto">Example Code</h4>
<p dir="auto"><code class="notranslate">print(pd.DataFrame({'a': np.zeros(1000, 'V4')}))</code></p>
<h4 dir="auto">Results</h4>
<p dir="auto">Non-deterministic behavior.  Sometimes you get all zeros, sometimes you get garbage like this:</p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="                        a
0            [1, 0, 0, 0]
1            [0, 0, 0, 0]
2            [8, 0, 0, 0]
3            [0, 0, 0, 0]
4      [48, -92, 71, -60]
5        [-27, 127, 0, 0]
6            [5, 0, 0, 0]
7            [0, 0, 0, 0]
..."><pre class="notranslate"><code class="notranslate">                        a
0            [1, 0, 0, 0]
1            [0, 0, 0, 0]
2            [8, 0, 0, 0]
3            [0, 0, 0, 0]
4      [48, -92, 71, -60]
5        [-27, 127, 0, 0]
6            [5, 0, 0, 0]
7            [0, 0, 0, 0]
...
</code></pre></div>
<p dir="auto">That is despite the fact that the bytes are actually all zero, and NumPy prints all rows as <code class="notranslate">[0, 0, 0, 0]</code>.</p>
<p dir="auto">Sometimes when printing a wider DataFrame containing such a column, it segfaults with this stack trace:</p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="#0  BYTE_copyswap (dst=0x7fffebdbe868, src=0x7fffe9f0d054, __NPY_UNUSED_TAGGEDswap=0, __NPY_UNUSED_TAGGEDarr=0x7fffea15f990)
    at numpy/core/src/multiarray/arraytypes.c.src:1911
#1  0x00007ffff5d82075 in PyArray_Scalar (data=0x7fffe9f0d054, descr=0x7fffea1612d0, base=&lt;optimized out&gt;) at numpy/core/src/multiarray/scalarapi.c:835
#2  0x00007ffff5d52df0 in array_item (self=0x7fffea15f990, i=&lt;optimized out&gt;) at numpy/core/src/multiarray/mapping.c:1371"><pre class="notranslate"><code class="notranslate">#0  BYTE_copyswap (dst=0x7fffebdbe868, src=0x7fffe9f0d054, __NPY_UNUSED_TAGGEDswap=0, __NPY_UNUSED_TAGGEDarr=0x7fffea15f990)
    at numpy/core/src/multiarray/arraytypes.c.src:1911
#1  0x00007ffff5d82075 in PyArray_Scalar (data=0x7fffe9f0d054, descr=0x7fffea1612d0, base=&lt;optimized out&gt;) at numpy/core/src/multiarray/scalarapi.c:835
#2  0x00007ffff5d52df0 in array_item (self=0x7fffea15f990, i=&lt;optimized out&gt;) at numpy/core/src/multiarray/mapping.c:1371
</code></pre></div>
<h4 dir="auto">Expected Output</h4>
<p dir="auto">All rows <code class="notranslate">[0, 0, 0, 0]</code> - just as NumPy prints it.</p>
<h4 dir="auto">Output of <code class="notranslate">pd.show_versions()</code></h4>
<details>
## INSTALLED VERSIONS
<p dir="auto">commit: None<br>
python: 3.5.1<br>
python-bits: 64<br>
OS: Linux<br>
OS-release: 3.13.0<br>
machine: x86_64<br>
processor: x86_64<br>
byteorder: little<br>
LC_ALL: None<br>
LANG: en_US.UTF-8</p>
<p dir="auto">pandas: 0.18.1<br>
pip: 8.1.2<br>
setuptools: 27.2.0<br>
numpy: 1.11.1</p>
</details>
<p dir="auto">Trying to print anything containing a V* (void) type throws in <code class="notranslate">isnull</code>:</p>
<div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="&gt;&gt;&gt; import numpy as np
&gt;&gt;&gt; import pandas as pd
&gt;&gt;&gt; arr = np.array([b'foo'], dtype='V')
&gt;&gt;&gt; arr
array([[102 111 111]],
      dtype='|V3')
&gt;&gt;&gt; s = pd.Series(arr)
&gt;&gt;&gt; s[0]
[102 111 111]
&gt;&gt;&gt; s
TypeError: ufunc 'isnan' not supported for the input types, and the inputs could 
not be safely coerced to any supported types according to the casting rule ''safe''"><pre class="notranslate"><span class="pl-c1">&gt;&gt;</span><span class="pl-c1">&gt;</span> <span class="pl-k">import</span> <span class="pl-s1">numpy</span> <span class="pl-k">as</span> <span class="pl-s1">np</span>
<span class="pl-c1">&gt;&gt;</span><span class="pl-c1">&gt;</span> <span class="pl-k">import</span> <span class="pl-s1">pandas</span> <span class="pl-k">as</span> <span class="pl-s1">pd</span>
<span class="pl-c1">&gt;&gt;</span><span class="pl-c1">&gt;</span> <span class="pl-s1">arr</span> <span class="pl-c1">=</span> <span class="pl-s1">np</span>.<span class="pl-en">array</span>([<span class="pl-s">b'foo'</span>], <span class="pl-s1">dtype</span><span class="pl-c1">=</span><span class="pl-s">'V'</span>)
<span class="pl-c1">&gt;&gt;</span><span class="pl-c1">&gt;</span> <span class="pl-s1">arr</span>
<span class="pl-en">array</span>([[<span class="pl-c1">102</span> <span class="pl-c1">111</span> <span class="pl-c1">111</span>]],
      <span class="pl-s1">dtype</span><span class="pl-c1">=</span><span class="pl-s">'|V3'</span>)
<span class="pl-c1">&gt;&gt;</span><span class="pl-c1">&gt;</span> <span class="pl-s1">s</span> <span class="pl-c1">=</span> <span class="pl-s1">pd</span>.<span class="pl-v">Series</span>(<span class="pl-s1">arr</span>)
<span class="pl-c1">&gt;&gt;</span><span class="pl-c1">&gt;</span> <span class="pl-s1">s</span>[<span class="pl-c1">0</span>]
[<span class="pl-c1">102</span> <span class="pl-c1">111</span> <span class="pl-c1">111</span>]
<span class="pl-c1">&gt;&gt;</span><span class="pl-c1">&gt;</span> <span class="pl-s1">s</span>
<span class="pl-v">TypeError</span>: <span class="pl-s1">ufunc</span> <span class="pl-s">'isnan'</span> <span class="pl-c1">not</span> <span class="pl-s1">supported</span> <span class="pl-k">for</span> <span class="pl-s1">the</span> <span class="pl-s1">input</span> <span class="pl-s1">types</span>, <span class="pl-c1">and</span> <span class="pl-s1">the</span> <span class="pl-s1">inputs</span> <span class="pl-s1">could</span> 
<span class="pl-c1">not</span> <span class="pl-s1">be</span> <span class="pl-s1">safely</span> <span class="pl-s1">coerced</span> <span class="pl-s1">to</span> <span class="pl-s1">any</span> <span class="pl-s1">supported</span> <span class="pl-s1">types</span> <span class="pl-s1">according</span> <span class="pl-s1">to</span> <span class="pl-s1">the</span> <span class="pl-s1">casting</span> <span class="pl-s1">rule</span> <span class="pl-s">''</span><span class="pl-s1">safe</span><span class="pl-s">''</span></pre></div>
<p dir="auto">From the looks of it, <code class="notranslate">pandas.core.common._isnull_ndarraylike</code> (and maybe some other methods?) should take care of this, e.g. return an array filled with False.</p>
<p dir="auto">Here's the relevant part of the traceback:</p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="pandas/formats/format.py in _format_strings(self)
   2057             vals = vals._values
   2058
-&gt; 2059         is_float = lib.map_infer(vals, com.is_float) &amp; notnull(vals)
   2060         leading_space = is_float.any()
   2061

pandas/core/common.py in notnull(obj)
    248     pandas.isnull : boolean inverse of pandas.notnull
    249     &quot;&quot;&quot;
--&gt; 250     res = isnull(obj)
    251     if lib.isscalar(res):
    252         return not res

pandas/core/common.py in isnull(obj)
     89     pandas.notnull: boolean inverse of pandas.isnull
     90     &quot;&quot;&quot;
---&gt; 91     return _isnull(obj)
     92
     93

pandas/core/common.py in _isnull_new(obj)
     99         raise NotImplementedError(&quot;isnull is not defined for MultiIndex&quot;)
    100     elif isinstance(obj, (gt.ABCSeries, np.ndarray, pd.Index)):
--&gt; 101         return _isnull_ndarraylike(obj)
    102     elif isinstance(obj, gt.ABCGeneric):
    103         return obj._constructor(obj._data.isnull(func=isnull))

pandas/core/common.py in _isnull_ndarraylike(obj)
    190         result = values.view('i8') == tslib.iNaT
    191     else:
--&gt; 192         result = np.isnan(values)
    193
    194     # box

TypeError: ufunc 'isnan' not supported for the input types, and the inputs could 
not be safely coerced to any supported types according to the casting rule ''safe''"><pre class="notranslate"><code class="notranslate">pandas/formats/format.py in _format_strings(self)
   2057             vals = vals._values
   2058
-&gt; 2059         is_float = lib.map_infer(vals, com.is_float) &amp; notnull(vals)
   2060         leading_space = is_float.any()
   2061

pandas/core/common.py in notnull(obj)
    248     pandas.isnull : boolean inverse of pandas.notnull
    249     """
--&gt; 250     res = isnull(obj)
    251     if lib.isscalar(res):
    252         return not res

pandas/core/common.py in isnull(obj)
     89     pandas.notnull: boolean inverse of pandas.isnull
     90     """
---&gt; 91     return _isnull(obj)
     92
     93

pandas/core/common.py in _isnull_new(obj)
     99         raise NotImplementedError("isnull is not defined for MultiIndex")
    100     elif isinstance(obj, (gt.ABCSeries, np.ndarray, pd.Index)):
--&gt; 101         return _isnull_ndarraylike(obj)
    102     elif isinstance(obj, gt.ABCGeneric):
    103         return obj._constructor(obj._data.isnull(func=isnull))

pandas/core/common.py in _isnull_ndarraylike(obj)
    190         result = values.view('i8') == tslib.iNaT
    191     else:
--&gt; 192         result = np.isnan(values)
    193
    194     # box

TypeError: ufunc 'isnan' not supported for the input types, and the inputs could 
not be safely coerced to any supported types according to the casting rule ''safe''
</code></pre></div>