blocks|key|1929737|text|正如@darthbaba正确指出的那样，pyalluvial期望数据格式由匹配不同可变类型组合的频率组成。为了给出一个有效输入的示例，每个Group中的每个Group都被标记为存在(1)或缺席(0)：|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|1929738|df+=+pd.DataFrame({
++++'Group':+[1]+*+6+%2B+[2]+*+6+%2B+[3]+*+6,
++++'Point+1':+[1,+1,+1,+1,+0,+0]+*+3,
++++'Point+2':+[0,+1,+0,+1,+1,+0]+*+3,
++++'Point+3':+[0,+0,+1,+1,+1,+1]+*+3,
++++'freq':+[23,+11,+5,+7,+10,+12,+17,+3,+6,+17,+19,+20,+28,+4,+13,+8,+14,+9]
++++})

fig+=+alluvial.plot(df=df,+xaxis_names=['Point+1','Point+2',+'Point+3'],+y_name='freq',+alluvium='Group',+ignore_continuity=False)|code-block|syntax|javascript|1929739|​|1929740|📷|atomic|1929741|1929742|显然，上面的代码并没有解决这个问题，因为pyalluvial还没有支持包含堆叠条，就像它是如何在ggalluvial中实现的(看见示例5)。因此，除非您想使用ggalluvial，否则IMO最好的选择是自己添加所需的功能。我从修改第85行开始。|1929743|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://developer.qcloudimg.com/http-save/yehe-900000/33a5bd1aed616bc22657798a10c48e1d.png|imageAlt|1|LINK|MUTABLE|url|https://cran.r-project.org/web/packages/ggalluvial/vignettes/ggalluvial.html|2|https://github.com/nekoumei/pyalluvial/blob/master/pyalluvial/alluvial.py^0|K|A|1X|5|26|5|2J|1|2P|1|0|0|0|0|1|0|0|0|K|A|1C|A|27|A|1R|2|1|37|4|2|0^^$0|@$1|2|3|4|5|6|7|18|8|@$9|19|A|1A|B|C]|$9|1B|A|1C|B|C]|$9|1D|A|1E|B|C]|$9|1F|A|1G|B|C]|$9|1H|A|1I|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|1J|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|1K|8|@]|D|@]|E|$]]|$1|M|3|N|5|O|7|1L|8|@]|D|@$9|1M|A|1N|1|1O]]|E|$]]|$1|P|3|L|5|6|7|1P|8|@]|D|@]|E|$]]|$1|Q|3|R|5|6|7|1Q|8|@$9|1R|A|1S|B|C]|$9|1T|A|1U|B|C]|$9|1V|A|1W|B|C]]|D|@$9|1X|A|1Y|1|1Z]|$9|20|A|21|1|22]]|E|$]]|$1|S|3|-4|5|6|7|23|8|@]|D|@]|E|$]]]|T|$U|$5|V|W|X|E|$Y|Z|10|-4]]|11|$5|12|W|13|E|$14|15]]|16|$5|12|W|13|E|$14|17]]]]

As correctly pointed out by @darthbaba, <code>pyalluvial</code> expects the dataframe format to consist of frequencies matching different variable-type combinations. To give you an example of a valid input, each <code>Point</code> in each <code>Group</code> has been labelled as present (<code>1</code>) or absent (<code>0</code>):
<pre><code>df = pd.DataFrame({
 'Group': [1] * 6 + [2] * 6 + [3] * 6,
 'Point 1': [1, 1, 1, 1, 0, 0] * 3,
 'Point 2': [0, 1, 0, 1, 1, 0] * 3,
 'Point 3': [0, 0, 1, 1, 1, 1] * 3,
 'freq': [23, 11, 5, 7, 10, 12, 17, 3, 6, 17, 19, 20, 28, 4, 13, 8, 14, 9]
 })

fig = alluvial.plot(df=df, xaxis_names=['Point 1','Point 2', 'Point 3'], y_name='freq', alluvium='Group', ignore_continuity=False)
</code></pre>
<a href="https://i.stack.imgur.com/FbV3H.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/FbV3H.png" alt="enter image description here" /></a>
Clearly, the above code doesn't resolve the issue since <code>pyalluvial</code> has yet to support the inclusion of stacked bars, much like how it's implemented in <code>ggalluvial</code> (<a href="https://cran.r-project.org/web/packages/ggalluvial/vignettes/ggalluvial.html" rel="nofollow noreferrer">see</a> example #5). Therefore, unless you want to use <code>ggalluvial</code>, your best option IMO is to add the required functionality yourself. I'd start by modifying <a href="https://github.com/nekoumei/pyalluvial/blob/master/pyalluvial/alluvial.py" rel="nofollow noreferrer">line #85</a>.

Surprisingly little info out there regarding python and the pyalluvial package. I'm hoping to combine stacked bars and a corresponding alluvial in the same figure.
Using below, I have three unique groups, which is outlined in <code>Group</code>. I want to display the proportion of each <code>Group</code> for each unique <code>Point</code>. I have the data formatted this way as I need three separate stacked bar charts for each <code>Point</code>.
So overall (<code>Ove</code>) highlight the overall proportion taken from all three <code>Points</code>. <code>Group 1</code> makes up 70%, <code>Group 2</code> makes up 20%, <code>Group 3</code> makes up 10%. But the proportion of each group changes at different intervals <code>Points</code>. I'm hoping to show this like a standard stacked bar chart, but add the alluvial over the top.
<pre><code>import pandas as pd
import pyalluvial.alluvial as alluvial 

df = pd.DataFrame({
 'Group': [1, 2, 3],
 'Ove': [0.7, 0.2, 0.1],
 'Point 1': [0.8, 0.1, 0.1],
 'Point 2': [0.6, 0.2, 0.2],
 'Point 3': [0.7, 0.3, 0.0],
 })

ax = alluvial.plot(
 df = df, 
 xaxis_names = ['Group','Point 1','Point 2', 'Point 3'], 
 y_name = 'Ove', 
 alluvium = 'Group',
)
</code></pre>
Output shows the overall group proportion (1st bar) being correct. But the following stacked bars with the proportions.
If I transform the df and put the Points as a single column, then I don't get 3 separate bars.
<a href="https://i.stack.imgur.com/9l4Yv.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/9l4Yv.png" alt="enter image description here" /></a>

stacked chart combine with alluvial plot - python

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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