<p>您可以将更快的<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.nlargest.html" rel="nofollow noreferrer">^{<cd1>}</a>用于顶部<code>5</code>行,然后使用<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.iterrows.html" rel="nofollow noreferrer">^{<cd3>}</a>和{a3}:</p>
<pre><code>import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
df = pd.read_csv('for_stack_nums')
#print (df.head())
top_5 = df[['High','Low','# of Trades']].nlargest(5, '# of Trades')
print (top_5)
High Low # of Trades
94 164.88 164.84 470
90 164.90 164.86 465
93 164.90 164.86 431
89 164.87 164.83 427
65 164.60 164.56 332
axnum = df[['High','Low']].plot()
axnum.yaxis.set_major_formatter(ticker.FormatStrFormatter('%.2f'))
for idx, l in top_5.iterrows():
plt.axhline(y=l['High'], color='r')
plt.axhline(y=l['Low'], color='b')
plt.show()
</code></pre>
<p><a href="https://i.stack.imgur.com/jD9Y2.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/jD9Y2.png" alt="graph"/></a></p>
<p>也不需要子集:</p>
^{pr2}$