<p dir="auto">Since I updated my pandas lib, I can't do this anymore</p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="db = pandas.HDFStore(path)
df = db.get('x')
df = df[['a', 'b', 'c']]"><pre class="notranslate"><code class="notranslate">db = pandas.HDFStore(path)
df = db.get('x')
df = df[['a', 'b', 'c']]
</code></pre></div>
<p dir="auto">It throw me Exception('Reindexing only valid with uniquely valued Index objects',)</p>
<p dir="auto">Mrknacky</p>
<div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="import pandas as pd
a = pd.TimedeltaIndex(range(3),unit='S')
print (a[1])"><pre class="notranslate"><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-s1">a</span> <span class="pl-c1">=</span> <span class="pl-s1">pd</span>.<span class="pl-v">TimedeltaIndex</span>(<span class="pl-en">range</span>(<span class="pl-c1">3</span>),<span class="pl-s1">unit</span><span class="pl-c1">=</span><span class="pl-s">'S'</span>)
<span class="pl-en">print</span> (<span class="pl-s1">a</span>[<span class="pl-c1">1</span>])</pre></div>
<p dir="auto">gives output</p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="11574 days 01:46:40"><pre class="notranslate"><code class="notranslate">11574 days 01:46:40
</code></pre></div>
<p dir="auto">I would expect the same output as from</p>
<div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="import pandas as pd
import numpy as np
npa = np.array(range(3),dtype='timedelta64[s]')
a = pd.TimedeltaIndex(npa)
print(a[1])"><pre class="notranslate"><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-k">import</span> <span class="pl-s1">numpy</span> <span class="pl-k">as</span> <span class="pl-s1">np</span>
<span class="pl-s1">npa</span> <span class="pl-c1">=</span> <span class="pl-s1">np</span>.<span class="pl-en">array</span>(<span class="pl-en">range</span>(<span class="pl-c1">3</span>),<span class="pl-s1">dtype</span><span class="pl-c1">=</span><span class="pl-s">'timedelta64[s]'</span>)
<span class="pl-s1">a</span> <span class="pl-c1">=</span> <span class="pl-s1">pd</span>.<span class="pl-v">TimedeltaIndex</span>(<span class="pl-s1">npa</span>)
<span class="pl-en">print</span>(<span class="pl-s1">a</span>[<span class="pl-c1">1</span>])</pre></div>
<p dir="auto">giving output</p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content=" 0 days 00:00:01"><pre class="notranslate"><code class="notranslate"> 0 days 00:00:01
</code></pre></div>
<p dir="auto">This is pandas 0.15.1 as installed by conda update pandas from a fresh python 3.4 install of anaconda.</p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="
INSTALLED VERSIONS
------------------
commit: None
python: 3.4.1.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 58 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: nb_NO

pandas: 0.15.1
nose: 1.3.4
Cython: 0.21
numpy: 1.9.1
scipy: 0.14.0
statsmodels: 0.5.0
IPython: 2.2.0
sphinx: 1.2.3
patsy: 0.3.0
dateutil: 2.1
pytz: 2014.9
bottleneck: None
tables: 3.1.1
numexpr: 2.3.1
matplotlib: 1.4.0
openpyxl: 1.8.5
xlrd: 0.9.3
xlwt: None
xlsxwriter: 0.5.7
lxml: 3.4.0
bs4: 4.3.2
html5lib: None
httplib2: None
apiclient: None
rpy2: None
sqlalchemy: 0.9.7
pymysql: None
psycopg2: None"><pre class="notranslate"><code class="notranslate">
INSTALLED VERSIONS
------------------
commit: None
python: 3.4.1.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 58 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: nb_NO

pandas: 0.15.1
nose: 1.3.4
Cython: 0.21
numpy: 1.9.1
scipy: 0.14.0
statsmodels: 0.5.0
IPython: 2.2.0
sphinx: 1.2.3
patsy: 0.3.0
dateutil: 2.1
pytz: 2014.9
bottleneck: None
tables: 3.1.1
numexpr: 2.3.1
matplotlib: 1.4.0
openpyxl: 1.8.5
xlrd: 0.9.3
xlwt: None
xlsxwriter: 0.5.7
lxml: 3.4.0
bs4: 4.3.2
html5lib: None
httplib2: None
apiclient: None
rpy2: None
sqlalchemy: 0.9.7
pymysql: None
psycopg2: None
</code></pre></div>