擅长:python、mysql、java
<p>那么追踪显示,</p>
<pre><code>df.resample('5H')['Bools'].sum == Groupby.sum (in pd.core.groupby.generic.SeriesGroupBy)
</code></pre>
<pre><code>df.resample('5H').sum == sum (in pandas.core.resample.DatetimeIndexResampler)
</code></pre>
<p>在<a href="https://github.com/pandas-dev/pandas/blob/v1.0.5/pandas/core/groupby/groupby.py" rel="nofollow noreferrer">groupby.py</a>中跟踪<code>groupby_function</code>表明它相当于
<code>r.agg(lambda x: np.sum(x, axis=r.axis))</code>
其中<code>r = df.resample('5H')</code>输出:</p>
<pre><code> Bools Nums Nums2
2020-01-01 05:00:00 2 10 10
2020-01-01 10:00:00 2 35 35
</code></pre>
<p>实际上,它应该是<code>r = df.resample('5H')['Bool']</code>(仅适用于上述情况)</em></p>
<p>追踪<a href="https://github.com/pandas-dev/pandas/blob/v1.0.5/pandas/core/resample.py" rel="nofollow noreferrer">resample.py</a>中的<code>_downsample</code>函数可以发现它相当于:
<code>df.groupby(r.grouper, axis=r.axis).agg(np.sum)</code>输出:</p>
<pre><code> Nums Nums2
2020-01-01 05:00:00 10 10
2020-01-01 10:00:00 35 35
</code></pre>