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NetworkX: list of directed edges in a triad census


Get the list of Triad nodes , who fall under the category of individual Triadic CensusHow do I check if a list is empty?Finding the index of an item given a list containing it in PythonDifference between append vs. extend list methods in PythonGetting the last element of a list in PythonHow to make a flat list out of list of lists?How do I get the number of elements in a list in Python?How do I concatenate two lists in Python?How to clone or copy a list?How do I list all files of a directory?How to read a file line-by-line into a list?






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1















In NetworkX, I can use the nx.triadic_census(g) to give me a list of triads in my network. enter image description here



Out:
'003': 1434217,
'012': 282025,
'102': 32640,
'021D': 21,
'021U': 267246,
'021C': 445


I wanted to know how I can list the directed edges belonging to a triad. For example, in Pyspark, to list the nodes/edges in triad "102" : g.find("(a)-[e]->(b); (b)-[e2]->(a)").show()



and it will give you





| a| e| b| e2|
+--------------------+-------------+--------------------+--------------+
|[US, United State...| [US, AZ, 0]| [AZ, Azerbaijan]| [AZ, US, 637]|
| [LU, Luxembourg]|[LU, BE, 213]| [BE, Belgium]|[BE, LU, 1470]|
| [FI, Finland]| [FI, CZ, 24]|[CZ, Czech Republic]| [CZ, FI, 51]|
| [HU, Hungary]| [HU, PL, 0]| [PL, Poland]| [PL, HU, 231]|
|[RU, Russian Fede...| [RU, UA, 0]| [UA, Ukraine]| [UA, RU, 0]|


Is there a way for me to do this in NetworkX?










share|improve this question




























    1















    In NetworkX, I can use the nx.triadic_census(g) to give me a list of triads in my network. enter image description here



    Out:
    '003': 1434217,
    '012': 282025,
    '102': 32640,
    '021D': 21,
    '021U': 267246,
    '021C': 445


    I wanted to know how I can list the directed edges belonging to a triad. For example, in Pyspark, to list the nodes/edges in triad "102" : g.find("(a)-[e]->(b); (b)-[e2]->(a)").show()



    and it will give you





    | a| e| b| e2|
    +--------------------+-------------+--------------------+--------------+
    |[US, United State...| [US, AZ, 0]| [AZ, Azerbaijan]| [AZ, US, 637]|
    | [LU, Luxembourg]|[LU, BE, 213]| [BE, Belgium]|[BE, LU, 1470]|
    | [FI, Finland]| [FI, CZ, 24]|[CZ, Czech Republic]| [CZ, FI, 51]|
    | [HU, Hungary]| [HU, PL, 0]| [PL, Poland]| [PL, HU, 231]|
    |[RU, Russian Fede...| [RU, UA, 0]| [UA, Ukraine]| [UA, RU, 0]|


    Is there a way for me to do this in NetworkX?










    share|improve this question
























      1












      1








      1








      In NetworkX, I can use the nx.triadic_census(g) to give me a list of triads in my network. enter image description here



      Out:
      '003': 1434217,
      '012': 282025,
      '102': 32640,
      '021D': 21,
      '021U': 267246,
      '021C': 445


      I wanted to know how I can list the directed edges belonging to a triad. For example, in Pyspark, to list the nodes/edges in triad "102" : g.find("(a)-[e]->(b); (b)-[e2]->(a)").show()



      and it will give you





      | a| e| b| e2|
      +--------------------+-------------+--------------------+--------------+
      |[US, United State...| [US, AZ, 0]| [AZ, Azerbaijan]| [AZ, US, 637]|
      | [LU, Luxembourg]|[LU, BE, 213]| [BE, Belgium]|[BE, LU, 1470]|
      | [FI, Finland]| [FI, CZ, 24]|[CZ, Czech Republic]| [CZ, FI, 51]|
      | [HU, Hungary]| [HU, PL, 0]| [PL, Poland]| [PL, HU, 231]|
      |[RU, Russian Fede...| [RU, UA, 0]| [UA, Ukraine]| [UA, RU, 0]|


      Is there a way for me to do this in NetworkX?










      share|improve this question














      In NetworkX, I can use the nx.triadic_census(g) to give me a list of triads in my network. enter image description here



      Out:
      '003': 1434217,
      '012': 282025,
      '102': 32640,
      '021D': 21,
      '021U': 267246,
      '021C': 445


      I wanted to know how I can list the directed edges belonging to a triad. For example, in Pyspark, to list the nodes/edges in triad "102" : g.find("(a)-[e]->(b); (b)-[e2]->(a)").show()



      and it will give you





      | a| e| b| e2|
      +--------------------+-------------+--------------------+--------------+
      |[US, United State...| [US, AZ, 0]| [AZ, Azerbaijan]| [AZ, US, 637]|
      | [LU, Luxembourg]|[LU, BE, 213]| [BE, Belgium]|[BE, LU, 1470]|
      | [FI, Finland]| [FI, CZ, 24]|[CZ, Czech Republic]| [CZ, FI, 51]|
      | [HU, Hungary]| [HU, PL, 0]| [PL, Poland]| [PL, HU, 231]|
      |[RU, Russian Fede...| [RU, UA, 0]| [UA, Ukraine]| [UA, RU, 0]|


      Is there a way for me to do this in NetworkX?







      python graph networkx






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked Mar 22 at 1:43









      noiivicenoiivice

      10611




      10611






















          1 Answer
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          There is no function in networkx that allow you to do it, so you should implement it manually. I modified the networkx.algorithms.triads code to return triad nodes, not their count. You can find it here. It can be modified with replacing tuple in census['...'].add(tuple(sorted([u, v, w]))) lines to add edges instead of nodes.






          share|improve this answer























          • i tried it out and it seemed to work. thanks.

            – noiivice
            Mar 28 at 16:05











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          active

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          There is no function in networkx that allow you to do it, so you should implement it manually. I modified the networkx.algorithms.triads code to return triad nodes, not their count. You can find it here. It can be modified with replacing tuple in census['...'].add(tuple(sorted([u, v, w]))) lines to add edges instead of nodes.






          share|improve this answer























          • i tried it out and it seemed to work. thanks.

            – noiivice
            Mar 28 at 16:05















          1














          There is no function in networkx that allow you to do it, so you should implement it manually. I modified the networkx.algorithms.triads code to return triad nodes, not their count. You can find it here. It can be modified with replacing tuple in census['...'].add(tuple(sorted([u, v, w]))) lines to add edges instead of nodes.






          share|improve this answer























          • i tried it out and it seemed to work. thanks.

            – noiivice
            Mar 28 at 16:05













          1












          1








          1







          There is no function in networkx that allow you to do it, so you should implement it manually. I modified the networkx.algorithms.triads code to return triad nodes, not their count. You can find it here. It can be modified with replacing tuple in census['...'].add(tuple(sorted([u, v, w]))) lines to add edges instead of nodes.






          share|improve this answer













          There is no function in networkx that allow you to do it, so you should implement it manually. I modified the networkx.algorithms.triads code to return triad nodes, not their count. You can find it here. It can be modified with replacing tuple in census['...'].add(tuple(sorted([u, v, w]))) lines to add edges instead of nodes.







          share|improve this answer












          share|improve this answer



          share|improve this answer










          answered Mar 27 at 22:48









          vurmuxvurmux

          469113




          469113












          • i tried it out and it seemed to work. thanks.

            – noiivice
            Mar 28 at 16:05

















          • i tried it out and it seemed to work. thanks.

            – noiivice
            Mar 28 at 16:05
















          i tried it out and it seemed to work. thanks.

          – noiivice
          Mar 28 at 16:05





          i tried it out and it seemed to work. thanks.

          – noiivice
          Mar 28 at 16:05



















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