<p>在master/0.13(很快发布)中,您可以这样做(在0.12中,这是一个手动操作,因为您必须在系列中单独执行)</p>
<pre><code>In [7]: df = DataFrame(np.random.randn(10000,2),index=date_range('20130101 09:00:00',periods=10000,freq='1Min'),columns=['last','volume'])
In [8]: df.info()
<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 10000 entries, 2013-01-01 09:00:00 to 2013-01-08 07:39:00
Freq: T
Data columns (total 2 columns):
last 10000 non-null values
volume 10000 non-null values
dtypes: float64(2)
In [9]: df.resample('1D',how='ohlc')
Out[9]:
last volume
open high low close open high low close
2013-01-01 0.801982 3.343166 -3.203291 -0.361502 0.255356 2.723863 -3.319414 1.073376
2013-01-02 0.101687 3.378843 -3.219792 -1.121900 1.226099 4.103099 -3.463014 -0.452594
2013-01-03 -0.051806 4.290010 -4.099700 -0.637321 0.713189 3.622728 -3.236652 -0.104458
2013-01-04 0.821215 3.058024 -3.907862 -1.595449 0.836234 2.821551 -3.191774 -0.399603
2013-01-05 0.084973 3.458210 -3.191455 1.426380 -0.402435 2.777447 -2.966165 1.227398
2013-01-06 -0.669922 3.232865 -3.902237 1.846017 -0.440055 3.088109 -3.710640 3.066725
2013-01-07 -0.122727 3.300163 -3.315501 1.718163 1.085066 3.373251 -4.029679 0.187828
2013-01-08 0.311785 3.073488 -3.013702 -0.627721 -0.502258 2.795292 -2.772738 -0.654676
[8 rows x 8 columns]
</code></pre>
<p>这将在0.12下工作</p>
^{pr2}$