擅长:python、mysql、java
<p>您可以使用<code>np.where()</code>:</p>
<p>导入数据:</p>
<pre><code>import sys
if sys.version_info[0] < 3:
from StringIO import StringIO
else:
from io import StringIO
data = StringIO('''Date,Location,NO2
2017-11-24 23:00:00,toronto,0.038
2017-11-24 22:00:00,toronto,0.031
2017-11-24 21:00:00,toronto,0.025
2017-11-24 20:00:00,toronto,0.033
2017-11-24 19:00:00,toronto,0.026
2017-11-24 18:00:00,toronto,0.021
2017-11-24 17:00:00,toronto,0.017''')
df = pd.read_csv(data, sep=',')
</code></pre>
<p>使用<code>np.where()</code>查找与max NO2值匹配的行的索引:</p>
<pre><code>max_time = df.loc[np.where(df.NO2.values == df.NO2.max())[0], 'Date'].values[0]
max_time = df.loc[np.where(df.NO2.values == df.NO2.max())[0], 'Date'].values[0]
print('Max time:',max_time)
print('Max NO2:',df.NO2.max())
</code></pre>
<pre><code>Max time: 2017-11-24 23:00:00
Max NO2: 0.038
</code></pre>