How to display a network with better separation using the Networkx package?

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I created a graph object using the pytextrank package like so:

import pytextrank

### ........................... 

### Some steps and calculations

### ...........................

graph, ranks = pytextrank.text_rank(path_stage1)

And I can use the networkx package to make a networkx drawing like so:

import networkx as nx

import matplotlib.pyplot as plt



fig = plt.figure(figsize=(50,50))

nx.draw(graph, with_labels=True) 



plt.show()

enter image description here

But as you can see, the words are mostly concentrated around the center. I would like to see higher separation between classes of words. How do I do that?

edited Jan 3 at 17:32

Anony-Mousse

59.3k797163

asked Jan 3 at 9:39

Kristada673

1,04411031

add a comment |

I created a graph object using the pytextrank package like so:

import pytextrank

### ........................... 

### Some steps and calculations

### ...........................

graph, ranks = pytextrank.text_rank(path_stage1)

And I can use the networkx package to make a networkx drawing like so:

import networkx as nx

import matplotlib.pyplot as plt



fig = plt.figure(figsize=(50,50))

nx.draw(graph, with_labels=True) 



plt.show()

enter image description here

But as you can see, the words are mostly concentrated around the center. I would like to see higher separation between classes of words. How do I do that?

edited Jan 3 at 17:32

Anony-Mousse

59.3k797163

asked Jan 3 at 9:39

Kristada673

1,04411031

add a comment |

I created a graph object using the pytextrank package like so:

import pytextrank

### ........................... 

### Some steps and calculations

### ...........................

graph, ranks = pytextrank.text_rank(path_stage1)

And I can use the networkx package to make a networkx drawing like so:

import networkx as nx

import matplotlib.pyplot as plt



fig = plt.figure(figsize=(50,50))

nx.draw(graph, with_labels=True) 



plt.show()

enter image description here

But as you can see, the words are mostly concentrated around the center. I would like to see higher separation between classes of words. How do I do that?

edited Jan 3 at 17:32

Anony-Mousse

59.3k797163

asked Jan 3 at 9:39

Kristada673

1,04411031

I created a graph object using the pytextrank package like so:

import pytextrank

### ........................... 

### Some steps and calculations

### ...........................

graph, ranks = pytextrank.text_rank(path_stage1)

And I can use the networkx package to make a networkx drawing like so:

import networkx as nx

import matplotlib.pyplot as plt



fig = plt.figure(figsize=(50,50))

nx.draw(graph, with_labels=True) 



plt.show()

enter image description here

But as you can see, the words are mostly concentrated around the center. I would like to see higher separation between classes of words. How do I do that?

python plot graph networkx graph-layout

edited Jan 3 at 17:32

Anony-Mousse

59.3k797163

asked Jan 3 at 9:39

Kristada673

1,04411031

edited Jan 3 at 17:32

Anony-Mousse

59.3k797163

asked Jan 3 at 9:39

Kristada673

1,04411031

edited Jan 3 at 17:32

Anony-Mousse

59.3k797163

edited Jan 3 at 17:32

Anony-Mousse

59.3k797163

edited Jan 3 at 17:32

Anony-Mousse

59.3k797163

asked Jan 3 at 9:39

Kristada673

1,04411031

asked Jan 3 at 9:39

Kristada673

1,04411031

asked Jan 3 at 9:39

Kristada673

1,04411031

add a comment |

1 Answer
1

active

oldest

votes

What you are looking for is a different layout (Networkx's term for node positioning algorithms that are used when drawing graphs). By default, nx.draw() is using spring layout. Changing your layout can be done as follows:

import networkx as nx

import matplotlib.pyplot as plt



fig = plt.figure(figsize=(50,50))

pos = nx.spectral_layout(graph)

nx.draw(graph, pos=pos, with_labels=True) 



plt.show()

You can play with a few layouts to find one that suits your needs.

Another option is to save your graph to a file, and load it with gephi, which has a nice GUI for visualizing and exploring your graph. (Also supporting several graph layout algorithms).

edited Jan 3 at 12:08

answered Jan 3 at 11:24

zohar.kom

1,1092720

add a comment |

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1 Answer
1

active

oldest

votes

1 Answer
1

active

oldest

votes

import networkx as nx

import matplotlib.pyplot as plt



fig = plt.figure(figsize=(50,50))

pos = nx.spectral_layout(graph)

nx.draw(graph, pos=pos, with_labels=True) 



plt.show()

You can play with a few layouts to find one that suits your needs.

Another option is to save your graph to a file, and load it with gephi, which has a nice GUI for visualizing and exploring your graph. (Also supporting several graph layout algorithms).

edited Jan 3 at 12:08

answered Jan 3 at 11:24

zohar.kom

1,1092720

add a comment |

import networkx as nx

import matplotlib.pyplot as plt



fig = plt.figure(figsize=(50,50))

pos = nx.spectral_layout(graph)

nx.draw(graph, pos=pos, with_labels=True) 



plt.show()

You can play with a few layouts to find one that suits your needs.

Another option is to save your graph to a file, and load it with gephi, which has a nice GUI for visualizing and exploring your graph. (Also supporting several graph layout algorithms).

edited Jan 3 at 12:08

answered Jan 3 at 11:24

zohar.kom

1,1092720

add a comment |

import networkx as nx

import matplotlib.pyplot as plt



fig = plt.figure(figsize=(50,50))

pos = nx.spectral_layout(graph)

nx.draw(graph, pos=pos, with_labels=True) 



plt.show()

You can play with a few layouts to find one that suits your needs.

Another option is to save your graph to a file, and load it with gephi, which has a nice GUI for visualizing and exploring your graph. (Also supporting several graph layout algorithms).

edited Jan 3 at 12:08

answered Jan 3 at 11:24

zohar.kom

1,1092720

import networkx as nx

import matplotlib.pyplot as plt



fig = plt.figure(figsize=(50,50))

pos = nx.spectral_layout(graph)

nx.draw(graph, pos=pos, with_labels=True) 



plt.show()

You can play with a few layouts to find one that suits your needs.

Another option is to save your graph to a file, and load it with gephi, which has a nice GUI for visualizing and exploring your graph. (Also supporting several graph layout algorithms).

edited Jan 3 at 12:08

answered Jan 3 at 11:24

zohar.kom

1,1092720

edited Jan 3 at 12:08

answered Jan 3 at 11:24

zohar.kom

1,1092720

answered Jan 3 at 11:24

zohar.kom

1,1092720

answered Jan 3 at 11:24

zohar.kom

1,1092720

add a comment |

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