blocks|key|164141|text|最好的方法是直接与axes对象交互|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|164142|import+numpy+as+np
import+matplotlib.pyplot+as+plt
x+=+np.arange(0,+10,+0.1)
y1+=+0.05+*+x**2
y2+=+-1+*y1

fig,+ax1+=+plt.subplots()

ax2+=+ax1.twinx()
ax1.plot(x,+y1,+'g-')
ax2.plot(x,+y2,+'b-')

ax1.set_xlabel('X+data')
ax1.set_ylabel('Y1+data',+color='g')
ax2.set_ylabel('Y2+data',+color='b')

plt.show()|code-block|syntax|javascript|164143|​|164144|📷|atomic|164145|164146|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/d5af8d70f1186430d7fe386eec025848.png|imageAlt^0|9|4|0|0|0|0|1|0|0|0^^$0|@$1|2|3|4|5|6|7|Z|8|@$9|10|A|11|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|12|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|13|8|@]|D|@]|E|$]]|$1|M|3|N|5|O|7|14|8|@]|D|@$9|15|A|16|1|17]]|E|$]]|$1|P|3|L|5|6|7|18|8|@]|D|@]|E|$]]|$1|Q|3|-4|5|6|7|19|8|@]|D|@]|E|$]]]|R|$S|$5|T|U|V|E|$W|X|Y|-4]]]]

The best way is to interact with the <code>axes</code> object directly

<pre><code>import numpy as np
import matplotlib.pyplot as plt
x = np.arange(0, 10, 0.1)
y1 = 0.05 * x**2
y2 = -1 *y1

fig, ax1 = plt.subplots()

ax2 = ax1.twinx()
ax1.plot(x, y1, 'g-')
ax2.plot(x, y2, 'b-')

ax1.set_xlabel('X data')
ax1.set_ylabel('Y1 data', color='g')
ax2.set_ylabel('Y2 data', color='b')

plt.show()
</code></pre>

<img src="https://i.stack.imgur.com/K7727.png" alt="example graph">

blocks|key|382037|text|我现在还不能访问Python，但在我的脑海中：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|382038|fig+=+plt.figure()

axes1+=+fig.add_subplot(111)
#+set+props+for+left+y-axis+here

axes2+=+axes1.twinx()+++#+mirror+them
axes2.set_ylabel(...)|code-block|syntax|javascript|382039|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

I don't have access to Python right now, but off the top of my head:

<pre><code>fig = plt.figure()

axes1 = fig.add_subplot(111)
# set props for left y-axis here

axes2 = axes1.twinx() # mirror them
axes2.set_ylabel(...)
</code></pre>

blocks|key|164183|text|有一个简单明了的解决方案，不用弄乱matplotlib:就是熊猫。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|164184|调整原始示例：|164185|table+=+sql.read_frame(query,connection)

ax+=+table[0].plot(color=colors[0],ylim=(0,100))
ax2+=+table[1].plot(secondary_y=True,color=colors[1],+ax=ax)

ax.set_ylabel('Left+axes+label')
ax2.set_ylabel('Right+axes+label')|code-block|syntax|javascript|164186|基本上，当给出secondary_y=True选项时(尽管也传递了ax=ax+)，pandas.plot返回一个不同的轴，我们用它来设置标签。|offset|length|style|CODE|164187|我知道这个问题很久以前就得到了回答，但我认为这种方法是值得的。|164188|entityMap^0|0|0|0|7|G|X|5|15|B|0|0^^$0|@$1|2|3|4|5|6|7|S|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|T|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|U|8|@]|9|@]|A|$G|H]]|$1|I|3|J|5|6|7|V|8|@$K|W|L|X|M|N]|$K|Y|L|Z|M|N]|$K|10|L|11|M|N]]|9|@]|A|$]]|$1|O|3|P|5|6|7|12|8|@]|9|@]|A|$]]|$1|Q|3|-4|5|6|7|13|8|@]|9|@]|A|$]]]|R|$]]

There is a straightforward solution without messing with matplotlib: just pandas.

Tweaking the original example:

<pre><code>table = sql.read_frame(query,connection)

ax = table[0].plot(color=colors[0],ylim=(0,100))
ax2 = table[1].plot(secondary_y=True,color=colors[1], ax=ax)

ax.set_ylabel('Left axes label')
ax2.set_ylabel('Right axes label')
</code></pre>

Basically, when the <code>secondary_y=True</code> option is given (eventhough <code>ax=ax</code> is passed too) <code>pandas.plot</code> returns a different axes which we use to set the labels.

I know this was answered long ago, but I think this approach worths it.

blocks|key|382120|text|对于因为提到了熊猫而偶然发现这篇文章的每个人来说，您现在有了一个非常优雅和直接的选择:在带有ax.right_ax的熊猫中使用directly+accessing+the+secondary_y+axis|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|382121|因此，根据最初发布的示例，您可以这样写：|382122|table+=+sql.read_frame(query,connection)

ax+=+table[[0,+1]].plot(ylim=(0,100),+secondary_y=table[1])
ax.set_ylabel('$')
ax.right_ax.set_ylabel('Your+second+Y-Axis+Label+goes+here!')|code-block|syntax|javascript|382123|(这些帖子中也提到了这一点：1+2)|382124|entityMap|0|LINK|mutability|MUTABLE|url|https://pandas.pydata.org/pandas-docs/stable/user_guide/visualization.html#plotting-on-a-secondary-y-axis|1|https://stackoverflow.com/a/58047785|2|https://stackoverflow.com/a/18078496^0|1A|B|1R|13|0|0|0|0|E|1|1|G|1|2|0^^$0|@$1|2|3|4|5|6|7|10|8|@$9|11|A|12|B|C]]|D|@$9|13|A|14|1|15]]|E|$]]|$1|F|3|G|5|6|7|16|8|@]|D|@]|E|$]]|$1|H|3|I|5|J|7|17|8|@]|D|@]|E|$K|L]]|$1|M|3|N|5|6|7|18|8|@]|D|@$9|19|A|1A|1|1B]|$9|1C|A|1D|1|1E]]|E|$]]|$1|O|3|-4|5|6|7|1F|8|@]|D|@]|E|$]]]|P|$Q|$5|R|S|T|E|$U|V]]|W|$5|R|S|T|E|$U|X]]|Y|$5|R|S|T|E|$U|Z]]]]

For everyone stumbling upon this post because pandas gets mentioned,
you now have the very elegant and straightforward option of <a href="https://pandas.pydata.org/pandas-docs/stable/user_guide/visualization.html#plotting-on-a-secondary-y-axis" rel="nofollow noreferrer">directly accessing the
secondary_y axis</a> in pandas with <code>ax.right_ax</code>
So paraphrasing the example initially posted, you would write:
<pre><code>table = sql.read_frame(query,connection)

ax = table[[0, 1]].plot(ylim=(0,100), secondary_y=table[1])
ax.set_ylabel('$')
ax.right_ax.set_ylabel('Your second Y-Axis Label goes here!')
</code></pre>
(this is already mentioned in these posts as well: <a href="https://stackoverflow.com/a/58047785">1</a> <a href="https://stackoverflow.com/a/18078496">2</a>)

blocks|key|164288|text|具有少量loc的简单示例：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|164289|plot(y1)
plt.gca().twinx().plot(y2,+color+=+'r')+#+default+color+is+same+as+first+ax|code-block|syntax|javascript|164290|解释：|164291|ax+=+plt.gca()++++#+Get+current+axis
ax2+=+ax.twinx()++#+make+twin+axis+based+on+x
ax2.plot(...)+++++#+...|164292|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|N|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|O|8|@]|9|@]|A|$]]|$1|I|3|J|5|D|7|P|8|@]|9|@]|A|$E|F]]|$1|K|3|-4|5|6|7|Q|8|@]|9|@]|A|$]]]|L|$]]

Simple example with few loc:
<pre class="lang-py prettyprint-override"><code>plot(y1)
plt.gca().twinx().plot(y2, color = 'r') # default color is same as first ax
</code></pre>
Explanation:
<pre class="lang-py prettyprint-override"><code>ax = plt.gca() # Get current axis
ax2 = ax.twinx() # make twin axis based on x
ax2.plot(...) # ...
</code></pre>

I can add a y label to the left y-axis using <code>plt.ylabel</code>, but how can I add it to the secondary y-axis?

<pre><code>table = sql.read_frame(query,connection)

table[0].plot(color=colors[0],ylim=(0,100))
table[1].plot(secondary_y=True,color=colors[1])
plt.ylabel('$')
</code></pre>

Adding a y-axis label to secondary y-axis in matplotlib

Python

我可以使用plt.ylabel将y标签添加到左侧y轴，但如何将其添加到第二个y轴？table = sql.read_frame(query,connection)table[0].plot(color=colors[0],ylim=(0,100))table[1].plot(secondary_y=True,color...

问在matplotlib中将y轴标签添加到辅助y轴
EN

社区

活动

资源

关于

腾讯云开发者

热门产品

热门推荐

更多推荐

问在matplotlib中将y轴标签添加到辅助y轴EN

社区

活动

资源

关于

腾讯云开发者

热门产品

热门推荐

更多推荐

问在matplotlib中将y轴标签添加到辅助y轴
EN