<p>我认为您需要在重新编制索引之前从列<code>Order_DateC</code>设置索引:</p>
<pre><code>CEITest = CEITest.set_index('Order_DateC')
</code></pre>
<p>最后,您可以通过<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.isnull.html" rel="nofollow">^{<cd3>}</a>和{a2}检查<code>notnull</code>值:</p>
^{pr2}$
<p>总而言之:</p>
<pre><code>print CEISales
Order_DateC RegionC SalesC
0 2014-01-30 Domestic 3530.00
1 2011-10-11 Domestic 136.00
2 1999-01-13 Domestic 30.00
3 1999-01-13 Domestic 55615.00
4 1999-01-13 Domestic 440.00
5 1999-01-13 Domestic 94.00
6 1999-01-05 Domestic 612.00
7 1999-01-14 Domestic 1067.00
8 1999-01-14 Domestic 26345.05
9 1999-01-15 Domestic 161858.72
CEIFilter = CEISales[CEISales['Order_DateC'] > '2010-01-01']
CEITest = CEIFilter.sort_values('Order_DateC')
print CEITest
Order_DateC RegionC SalesC
1 2011-10-11 Domestic 136
0 2014-01-30 Domestic 3530
#set index to datetimeindex
CEITest = CEITest.set_index('Order_DateC')
print CEITest
RegionC SalesC
Order_DateC
2011-10-11 Domestic 136
2014-01-30 Domestic 3530
date_index = pd.date_range(start='2010-01-01', end='2015-12-23' , freq='d')
</code></pre>
<pre><code>CEIFinal= CEITest.reindex(date_index)
print CEIFinal.head()
RegionC SalesC
2010-01-01 NaN NaN
2010-01-02 NaN NaN
2010-01-03 NaN NaN
2010-01-04 NaN NaN
2010-01-05 NaN NaN
</code></pre>
<p>可以有很多<code>Nat</code>和<code>NaN</code>,检查数据:</p>
<pre><code>print CEIFinal[CEIFinal.notnull().any(axis=1)]
RegionC SalesC
2011-10-11 Domestic 136
2014-01-30 Domestic 3530
</code></pre>
<p>最后,您可以设置索引名,<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.reset_index.html" rel="nofollow">^{<cd7>}</a>index-column name是索引名:</p>
<pre><code>CEIFinal.index.name = 'CEIFinal'
CEIFinal = CEIFinal.reset_index()
print CEIFinal.head()
CEIFinal RegionC SalesC
0 2010-01-01 NaN NaN
1 2010-01-02 NaN NaN
2 2010-01-03 NaN NaN
3 2010-01-04 NaN NaN
4 2010-01-05 NaN NaN
</code></pre>