entityMap|0|type|LINK|mutability|MUTABLE|data|url|https://pypi.org/project/graphviz/|blocks|key|bld9l|text|您还可以使用graphviz库：|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|ee5gh|from+graphviz+import+Digraph
dot+=+Digraph()

for+i,+(a,+b)+in+df.iterrows():
++++dot.edge(str(a),+str(b))
++++
dot.render('graph.gv',+view=True)|code-block|syntax|javascript|ch64u^0|6|8|6|8|0|0|0^^$0|$1|$2|3|4|5|6|$7|8]]]|9|@$A|B|C|D|2|E|F|S|G|@$H|T|I|U|J|K]]|L|@$H|V|I|W|A|X]]|6|$]]|$A|M|C|N|2|O|F|Y|G|@]|L|@]|6|$P|Q]]|$A|R|C|-4|2|E|F|Z|G|@]|L|@]|6|$]]]]

You can also use the <a href="https://pypi.org/project/graphviz/" rel="nofollow noreferrer"><code>graphviz</code></a> library:
<pre><code>from graphviz import Digraph
dot = Digraph()

for i, (a, b) in df.iterrows():
 dot.edge(str(a), str(b))
 
dot.render('graph.gv', view=True)
</code></pre>

entityMap|0|type|LINK|mutability|MUTABLE|data|url|https://networkx.org/documentation/stable/index.html|1|IMAGE|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/e4aab6c6d4a82204293adf331ce10f73.png|imageAlt|blocks|key|e1ilp|text|Networkx是python中的图形库：https://networkx.org/documentation/stable/index.html|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|5ccs4|首先进行导入：|65o1p|import+networkx+as+nx|code-block|syntax|javascript|1r2mu|要启动一个声明初始化DiGraph+(有向图)的图：|dt05n|G+=+nx.DiGraph()|djar0|然后添加一些节点：|5jia|G.add_node(343)
G.add_node(991)
G.add_node(633)|l34r|然后是一些边：|7as36|G.add_edge(343,991)
G.add_edge(991,633)
G.add_edge(343,633)|b64of|最后画出图G：|fd4qa|nx.draw(G,+with_labels+=+True,+font_size=14+,+node_size=2000)|fupfe|使用with_labels+=+True以获得节点编号，使用node_size=2000使节点变大，使用font_size=14使字体变大|7kkcv|这是代码的输出：|8fsvm|​|47o6v|?|atomic|4trm5|al93t|现在，要从数据帧中读取数据，只需执行如下循环：|5bqlv|for++i,+(x,+y)+in+df.iterrows():
++++G.add_node(x)
++++G.add_node(y)
++++G.add_edge(x,y)|4ns7u|如果结点或边已经存在，则不会添加新的结点或边，因此无需担心|ft8e7^0|L|1G|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|1|1|0|0|0|0|0^^$0|$1|$2|3|4|5|6|$7|8]]|9|$2|A|4|B|6|$C|D|E|-4]]]|F|@$G|H|I|J|2|K|L|1U|M|@]|N|@$O|1V|P|1W|G|1X]]|6|$]]|$G|Q|I|R|2|K|L|1Y|M|@]|N|@]|6|$]]|$G|S|I|T|2|U|L|1Z|M|@]|N|@]|6|$V|W]]|$G|X|I|Y|2|K|L|20|M|@]|N|@]|6|$]]|$G|Z|I|10|2|U|L|21|M|@]|N|@]|6|$V|W]]|$G|11|I|12|2|K|L|22|M|@]|N|@]|6|$]]|$G|13|I|14|2|U|L|23|M|@]|N|@]|6|$V|W]]|$G|15|I|16|2|K|L|24|M|@]|N|@]|6|$]]|$G|17|I|18|2|U|L|25|M|@]|N|@]|6|$V|W]]|$G|19|I|1A|2|K|L|26|M|@]|N|@]|6|$]]|$G|1B|I|1C|2|U|L|27|M|@]|N|@]|6|$V|W]]|$G|1D|I|1E|2|K|L|28|M|@]|N|@]|6|$]]|$G|1F|I|1G|2|K|L|29|M|@]|N|@]|6|$]]|$G|1H|I|1I|2|K|L|2A|M|@]|N|@]|6|$]]|$G|1J|I|1K|2|1L|L|2B|M|@]|N|@$O|2C|P|2D|G|2E]]|6|$]]|$G|1M|I|1I|2|K|L|2F|M|@]|N|@]|6|$]]|$G|1N|I|1O|2|K|L|2G|M|@]|N|@]|6|$]]|$G|1P|I|1Q|2|U|L|2H|M|@]|N|@]|6|$V|W]]|$G|1R|I|1S|2|K|L|2I|M|@]|N|@]|6|$]]|$G|1T|I|-4|2|K|L|2J|M|@]|N|@]|6|$]]]]

Networkx is the go-to library for graphs in python:
<a href="https://networkx.org/documentation/stable/index.html" rel="nofollow noreferrer">https://networkx.org/documentation/stable/index.html</a>
First do the import:
<pre><code>import networkx as nx
</code></pre>
To start a graph like that declare a inicialize DiGraph (directed graph):
<pre><code>G = nx.DiGraph()
</code></pre>
Then add some nodes:
<pre><code>G.add_node(343)
G.add_node(991)
G.add_node(633)
</code></pre>
Then some edges:
<pre><code>G.add_edge(343,991)
G.add_edge(991,633)
G.add_edge(343,633)
</code></pre>
Finaly draw the graph G:
<pre><code>nx.draw(G, with_labels = True, font_size=14 , node_size=2000)
</code></pre>
use the with_labels = True so you can have the node numbers, node_size=2000 to make the nodes bigger and font_size=14 to make the font also bigger
This is the output of the code:
<a href="https://i.stack.imgur.com/dkpi2.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/dkpi2.png" alt="This is the output of the code" /></a>
Now to read from the dataframe, just do a cycle like:
<pre><code>for i, (x, y) in df.iterrows():
 G.add_node(x)
 G.add_node(y)
 G.add_edge(x,y)
</code></pre>
If the nodes or edges already exists it will not add a new one, so you don't need to worry about it

Suppose I have this dataframe where column <code>a-number</code> represents nodes with directed edges to nodes in <code>b-number</code>:
<pre><code> a_number b_number
0 343 991
1 991 633
2 343 633
3 633 628
4 343 633
5 628 916
6 697 886
7 916 572
8 697 884
9 886 125
</code></pre>
How can I generate an image representation of this graph that looks like this:
<a href="https://i.stack.imgur.com/fkyde.jpg" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/fkyde.jpg" alt="enter image description here" /></a>

Generate Network plot from dataframe

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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 假设我有这样一个数据帧，其中列a-number表示到b-number中节点的有向边的节点     a_number    b_number0   343              9911   991              6332   343              6333   633           ...

问从数据帧生成网络图
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