擅长:python、mysql、java
<p>使用<a href="http://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Grouper.html" rel="nofollow noreferrer">^{<cd1>}</a>和<a href="http://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.core.groupby.GroupBy.last.html" rel="nofollow noreferrer">^{<cd2>}</a>,用<code>ffill</code>和<a href="http://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.reset_index.html" rel="nofollow noreferrer">^{<cd4>}</a>向前填充缺失的值:</p>
<pre><code>#if necessary
#df['date'] = pd.to_datetime(df['date'])
df = df.groupby(pd.Grouper(freq='m',key='date'))['totalShrs'].last().ffill().reset_index()
#alternative
#df = df.resample('m',on='date')['totalShrs'].last().ffill().reset_index()
print (df)
date totalShrs
0 2009-04-30 40000.0
1 2009-05-31 80000.0
2 2009-06-30 110000.0
3 2009-07-31 110000.0
4 2009-08-31 120000.0
</code></pre>