blocks|key|1771182|text|legend不适用于您的散点图，因为散点图创建了单个对象，并且只会在legend中显示为单个项。由于每个点的颜色取决于轴的颜色图，所以您需要使用colorbar|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|1771183|plt.colorbar(example)|code-block|syntax|javascript|1771184|如果您想要一个legend，则需要为每个组创建一个单独的散点图，然后根据它创建一个图例。这方面的一个例子是这里|1771185|entityMap|0|LINK|mutability|MUTABLE|url|http://matplotlib.org/api/figure_api.html#matplotlib.figure.Figure.colorbar|1|http://matplotlib.org/examples/lines_bars_and_markers/scatter_with_legend.html#lines-bars-and-markers-scatter-with-legend^0|0|6|Y|6|20|8|20|8|0|0|0|7|6|1H|2|1|0^^$0|@$1|2|3|4|5|6|7|W|8|@$9|X|A|Y|B|C]|$9|Z|A|10|B|C]|$9|11|A|12|B|C]]|D|@$9|13|A|14|1|15]]|E|$]]|$1|F|3|G|5|H|7|16|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|17|8|@$9|18|A|19|B|C]]|D|@$9|1A|A|1B|1|1C]]|E|$]]|$1|M|3|-4|5|6|7|1D|8|@]|D|@]|E|$]]]|N|$O|$5|P|Q|R|E|$S|T]]|U|$5|P|Q|R|E|$S|V]]]]

A <code>legend</code> won't work for your scatter plot because the scatter plot creates a single object and would only appear as a single item in a <code>legend</code>. Since the color of each point depends upon the colormap of the axes, you'll instead need to use a <a href="http://matplotlib.org/api/figure_api.html#matplotlib.figure.Figure.colorbar" rel="nofollow noreferrer"><code>colorbar</code></a> 

<pre><code>plt.colorbar(example)
</code></pre>

If you want a <code>legend</code> instead, you need to create a separate scatter plot for each group and then create a legend from that. An example of that is shown <a href="http://matplotlib.org/examples/lines_bars_and_markers/scatter_with_legend.html#lines-bars-and-markers-scatter-with-legend" rel="nofollow noreferrer">here</a>

blocks|key|550912|text|这是我个人在我所有的素材库传说中使用的东西。我通常将数据存储在dictionaries和pd.Series对象中。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|550913|def+get_legend_markers(D_label_color,+marker="o",+marker_kws={"linestyle":""}):
++++"""
++++Usage:+plt.legend(*legend_vars(D_taxon_color),
++++++++++++++++++++++loc="lower+center",
++++++++++++++++++++++bbox_to_anchor=(0.5,-0.15),
++++++++++++++++++++++fancybox=True,+shadow=True,
++++++++++++++++++++++prop={'size':15})

++++Input:+Dictionary+object+of+{label:color}
++++Output:+Tuple+of+markers+and+labels
++++"""
++++markers+=+[plt.Line2D([0,0],[0,0],color=color,+marker=marker,+**marker_kws)+for+color+in+D_label_color.values()]
++++return+(markers,+D_label_color.keys())|code-block|syntax|javascript|550914|这样你就可以像：|550915|D_label_color+=+{"A":"green",+"B":"blue",+"C":"red"}
fig,+ax+=+plt.subplots()
x+=+np.linspace(0,+2*np.pi)
y+=+np.sin(x)
c+=+["green"]*20+%2B+["blue"]*20+%2B+["red"]*10
ax.scatter(x=x,+y=y,+c=c)
ax.legend(*get_legend_markers(D_label_color)|550916|如果您不知道为哪个颜色分配了确切的颜色，可以使用seaborn对每个类别使用sns.color_palette(n_colors)为它们分配颜色，然后生成一个颜色列表/向量(如上面的c+)，然后给ax.scatter分配颜色。希望这能有所帮助。如果您处理的是连续数据，那么我将使用上面提到的@suever这样的颜色栏。你不可能真的有一个连续的数据图例。|550917|entityMap^0|V|C|18|9|0|0|0|0|O|7|12|R|2J|1|2Q|A|0^^$0|@$1|2|3|4|5|6|7|S|8|@$9|T|A|U|B|C]|$9|V|A|W|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|X|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|Y|8|@]|D|@]|E|$]]|$1|M|3|N|5|H|7|Z|8|@]|D|@]|E|$I|J]]|$1|O|3|P|5|6|7|10|8|@$9|11|A|12|B|C]|$9|13|A|14|B|C]|$9|15|A|16|B|C]|$9|17|A|18|B|C]]|D|@]|E|$]]|$1|Q|3|-4|5|6|7|19|8|@]|D|@]|E|$]]]|R|$]]

This is what I personally use for all of my matplotlib legends. I usually store my data in <code>dictionaries</code> and <code>pd.Series</code> objects. 

<pre><code>def get_legend_markers(D_label_color, marker="o", marker_kws={"linestyle":""}):
 """
 Usage: plt.legend(*legend_vars(D_taxon_color),
 loc="lower center",
 bbox_to_anchor=(0.5,-0.15),
 fancybox=True, shadow=True,
 prop={'size':15})

 Input: Dictionary object of {label:color}
 Output: Tuple of markers and labels
 """
 markers = [plt.Line2D([0,0],[0,0],color=color, marker=marker, **marker_kws) for color in D_label_color.values()]
 return (markers, D_label_color.keys())
</code></pre>

So you could something like: 

<pre><code>D_label_color = {"A":"green", "B":"blue", "C":"red"}
fig, ax = plt.subplots()
x = np.linspace(0, 2*np.pi)
y = np.sin(x)
c = ["green"]*20 + ["blue"]*20 + ["red"]*10
ax.scatter(x=x, y=y, c=c)
ax.legend(*get_legend_markers(D_label_color)
</code></pre>

If you don't know exactly which color is assigned to which point you can assign them with <code>seaborn</code> using <code>sns.color_palette(n_colors)</code> for each category and then make a list/vector of colors ( like <code>c</code> above ) and then give <code>ax.scatter</code> that color assignment. Hope this helps. If you're dealing with continuous data then i would go with a color bar like @suever mentioned above. You can't really have a legend with continuous data.

I cannot see to find (or figure out) how to show the legend using <code>pyplot.scatter()</code> when I've changed the labels to be numerical values. 

That is, I transformed my categorical values 'a', 'b', 'c', .. into 0, 1, 2, ...

<a href="http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.scatter" rel="nofollow noreferrer">http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.scatter</a>

Here is the example given on the URL above:

<pre><code>import numpy as np
import matplotlib.pyplot as plt

N = 50
x = np.random.rand(N)
y = np.random.rand(N)
colors = np.random.rand(N)
area = np.pi * (15 * np.random.rand(N))**2 # 0 to 15 point radii

plt.scatter(x, y, s=area, c=colors, alpha=0.5, cmap=cm.jet)
plt.show()
</code></pre>

which outputs <a href="https://i.stack.imgur.com/3HCZO.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/3HCZO.png" alt="enter image description here"></a>

Normally, I believe one would do something like this:

<pre><code>example = plt.scatter(x, y, s=area, c=colors, alpha=0.5, cmap=cm.jet)
plt.legend(handles=[example])
plt.show()
</code></pre>

This does not output a legend corresponding each color in the plot with the number in the array. 

<pre><code>/opt/local/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/matplotlib/axes/_axes.py:518: UserWarning: The handle &lt;matplotlib.collections.PathCollection object at 0x1167d03c8&gt; has a label of '_collection0' which cannot be automatically added to the legend.
 'legend.'.format(handle, label))
</code></pre>

How can I output a legend which shows which number corresponds with the array value?

How does one plot the legend with pyplot.scatter(), when the legend are only numerical values?

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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当我将标签更改为数值时，我看不出如何使用pyplot.scatter()来显示图例。也就是说，我转换了我的分类值'a'，'b'，'c'，变成0，1，2 .下面是上面URL上的示例：import numpy as npimport matplotlib.pyplot as pltN = 50x = np.random.r...

问当图例只是数值时，如何用pyplot.scatter()来绘制图例呢？
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问当图例只是数值时，如何用pyplot.scatter()来绘制图例呢？
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