Kev*_*vin 9 python networkx pandas
更新:
如编写的那样,问题与Networkx版本<2.0有关.该from_pandas_dataframe方法已被删除.
要在Networkx> = 2.0中完成相同的任务,请参阅对已接受答案的更新.
尝试MultiGraph()使用networkx从pandas DataFrame 创建实例from_pandas_dataframe.我在下面的例子中做错了什么?
In [1]: import pandas as pd
import networkx as nx
df = pd.DataFrame([['geneA', 'geneB', 0.05, 'method1'],
['geneA', 'geneC', 0.45, 'method1'],
['geneA', 'geneD', 0.35, 'method1'],
['geneA', 'geneB', 0.45, 'method2']],
columns = ['gene1','gene2','conf','type'])
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首先尝试使用默认的nx.Graph():
In [2]: G= nx.from_pandas_dataframe(df, 'gene1', 'gene2', edge_attr=['conf','type'],
create_using=nx.Graph())
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作为一个非MultiGraph(),我错过了一个重复的边:
In [3]: G.edges(data=True)
Out[3]: [('geneA', 'geneB', {'conf': 0.45, 'type': 'method2'}),
('geneA', 'geneC', {'conf': 0.45, 'type': 'method1'}),
('geneA', 'geneD', {'conf': 0.35, 'type': 'method1'})]
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用MultiGraph():
In [4]: MG= nx.from_pandas_dataframe(df, 'gene1', 'gene2', edge_attr=['conf','type'],
create_using=nx.MultiGraph())
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这个:
TypeError Traceback (most recent call last)
<ipython-input-49-d2c7b8312ea7> in <module>()
----> 1 MG= nx.from_pandas_dataframe(df, 'gene1', 'gene2', ['conf','type'], create_using=nx.MultiGraph())
/usr/lib/python2.7/site-packages/networkx-1.10-py2.7.egg/networkx/convert_matrix.pyc in from_pandas_dataframe(df, source, target, edge_attr, create_using)
209 # Iteration on values returns the rows as Numpy arrays
210 for row in df.values:
--> 211 g.add_edge(row[src_i], row[tar_i], {i:row[j] for i, j in edge_i})
212
213 # If no column names are given, then just return the edges.
/usr/lib/python2.7/site-packages/networkx-1.10-py2.7.egg/networkx/classes/multigraph.pyc in add_edge(self, u, v, key, attr_dict, **attr)
340 datadict.update(attr_dict)
341 keydict = self.edge_key_dict_factory()
--> 342 keydict[key] = datadict
343 self.adj[u][v] = keydict
344 self.adj[v][u] = keydict
TypeError: unhashable type: 'dict'
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问题
如何MultiGraph()从pandas数据框中实例化?
Networkx <2.0:
这是一个错误,我在GitHub上打开了一个问题,一旦我做了建议的编辑:
它将第211行更改convert_matrix.py为:
g.add_edge(row[src_i], row[tar_i], attr_dict={i:row[j] for i, j in edge_i})
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这一变化的结果:( 已被纳入)
MG= nx.from_pandas_dataframe(df, 'gene1', 'gene2', edge_attr=['conf','type'],
create_using=nx.MultiGraph())
MG.edges(data=True)
[('geneA', 'geneB', {'conf': 0.05, 'type': 'method1'}),
('geneA', 'geneB', {'conf': 0.45, 'type': 'method2'}),
('geneA', 'geneC', {'conf': 0.45, 'type': 'method1'}),
('geneA', 'geneD', {'conf': 0.35, 'type': 'method1'})]
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Networkx> = 2.0:
在具有此格式(边缘列表)的DataFrame中,使用from_pandas_edgelist
MG= nx.from_pandas_edgelist(df, 'gene1', 'gene2', edge_attr=['conf','type'],
create_using=nx.MultiGraph())
MG.edges(data=True)
MultiEdgeDataView([('geneA', 'geneB', {'conf': 0.05, 'type': 'method1'}),
('geneA', 'geneB', {'conf': 0.45, 'type': 'method2'}),
('geneA', 'geneC', {'conf': 0.45, 'type': 'method1'}),
('geneA', 'geneD', {'conf': 0.35, 'type': 'method1'})])
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